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Becker’s Healthcare Podcast
How Health Systems Can Validate ROI and Successfully Scale Ambient AI Solutions from Pilot Programs to Enterprise-Wide Impact
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- [00:00]
A
Hi everyone, this is Lucas Voss with Becker's Healthcare. Thanks so much for tuning in to the Beckers Healthcare podcast series. It's great to have you. Today we're talking about how health systems can validate ROI and successfully scale ambient AI solutions from pilot programs to enterprise wide impact. And joining me for today's discussion, very excited to have him is Mac Border Revenue Cycle Management and Business Solutions Research Director at CLAAS Research, and Josh Margulies, VP of Brand Advocacy at Suki AI. All right, Josh and Mac, it's so great to have you both. Thanks so much for taking some time to be here.
- [00:38]
B
Thanks for having us, Lucas. This is great.
- [00:40]
C
Yeah, glad to be here.
- [00:41]
A
Absolutely. Mac, I want to start us off with you again. Classes known around the healthcare space for that research, trusted independent voice, specifically in healthcare it obviously I want to know why third party ROI validation is so important right now, especially when we're looking at this crowded ambient AR market.
- [01:06]
C
It's a great question, Lucas, and frankly it's the question I get asked probably the most in the last six months or so, six to eight months from CMIO CIOs, but also of course CFOs who are probably the most concerned with the fiduciary aspect of, you know, any implementation. They're all asking the same thing. We understand that the ambient AI at this point it's relatively understood and the adoption is very positive. The reception from clinician users, physician users, very positive, very high. And we can talk about some of those reasons in a moment, but generally that's understood. What is less understood and is just as important is what are the financial, operational, clinical and patient benefits where we can draw that causative and correlative link between the adoption of these tools, the implementation of them properly and the roi. Like what can we draw and what are the specifics about it. So that's one of the number one things that I'm being asked about at class. And so this study with Suki, which was again with McLeod Health, FMOL Health and Rush University, was so essential because it gives you the perspective across very different health systems, but very strong health systems. All of these teams are excellent organizations already performing and doing well and to be able to see what they're doing from good to great. I think that was one of the, one of the key findings of the study that we were trying to put
- [02:25]
A
together and it's so crucial because it informs future strategy. It has such an impact on the future of these organizations. And I do want to go into a little bit more Detail on this recent research you've mentioned. Again, there's some striking numbers in there. 65% reduction in after hours documentation time, over $1,000 in monthly revenue, lift per provider. And Josh, I'll start off with you on this one. What surprised you most when you looked at those findings across ephemeral health, McLeod Health and Rush University?
- [02:57]
B
Yeah, there's a couple things. I mean, I think the obvious ones are a reduction in time and note and getting the seven day note closure down. And those things are massive. But the two that jump out to me are one, the revenue generated per clinician. Because a lot of these health systems went into this pilot or this project just to try to help clinicians. Right. And I know the CMIO really well at McLeod, Dr. Frost, and he was like, our goal is just to break even. That was our hope, right. We wanted to improve the lives of clinicians. We wanted to break even. And the fact that they can attribute, you know, somewhere between $1,020 $600 a month per clinician is of additional ROI is just incredible. Right. It's really kind of the. It was the unexpected benefit that we love to see. The other side of that that I think I'm most excited about personally is the patient satisfaction number. So this was a really interesting one that they do patient satisfaction through a third. They said at best when we make changes, we get a 1% bump in something. But they got a 6% increase in probably the two most important questions that are asked of patients. Do you trust your provider and did you feel heard? Right. And those two things went up between five and a half and six and a half percent. And they said, we've never seen that in the history of doing these surveys, we've never seen that. And it just goes to show you the value of eye contact, the value of treating patients like humans. Right. And clinicians want to be eye to eye, knee to knee. It was always their goal. They got into this profession as a calling because they care deeply about healing people. And all the administrative tasks took them away from that. And so it's so awesome to see that while this tool was created for clinicians, the biggest outcome is not just clinicians, but it's patient care and patient satisfaction. And that's super rewarding.
- [04:54]
C
Yeah.
- [04:54]
A
Again, it's that trickle down effect, Right. That Mac talked about it in the beginning of our conversation here. Right. How important it is to be able to validate all of this and being able to connect the dots to some of these things. Mac, I'd love to know too. Was there anything that stuck out to you when you were looking at the numbers and the research?
- [05:10]
C
Yeah, for sure. So as we looked at the three different organizations, and again, they're all very different, all very excellent teams, but they came at the pilots differently, they engaged their own teams internally differently. So anything that showed up across all three systems, that really stood out to me. And one of those beyond time savings, which all three organizations reported, we also saw improved documentation or coding uplift. So the improved E M coding, people think again about the documentation being complete and accurate. And it needs to be not just for the most important thing, which is again, patient outcomes, ensuring we don't misread something or give an order incorrectly for a medication. That's essential, as we can all agree, we're all patients, we all understand that need. But I think the improvement in documentation and coding wasn't, again, to Josh's point, it maybe wasn't the top priority for a lot of these teams, but once they saw that impact, that downstream impact through the revenue cycle process and all the way through to billing, it becomes then, wow, we can actually draw direct engagement here. And again, all three teams, McLeod, Rush, FMOL, all reported improved documentation and coding up list. So anything that stood out to me, those are a couple of things that stood out to me. There were some other things as well if we had time, but I think really those were the two that you want to see across all three very different systems that to me stands out and that becomes really impactful.
- [06:33]
A
It's that read through line for all of them which is so crucial. Again, it shows the impact, it's clearly there. And Josh, I want to talk a little bit more specifically about Suki and some of the achievements that you've made here throughout your time there. And certainly again, we see a lot of health systems running ambient AI pilots, right. We know they're popular, everybody's trying them, but again, a lot of these organizations struggle to then actually say, okay, it's kind of worked, but there is really no enterprise wide business case or scalable impact. Right. From Suki's perspective. From your perspective, Right. How did Suki's customers then make that leap to say, okay, this is scalable, it's making an enterprise wide impact, and what did they do differently to get those outcomes?
- [07:20]
B
Yeah, there's a lot to unpack with that question. It's a great question. I think there's a couple things that jump out to me. First, I think that one of the things I've been most proud of with Suki, is that we are very, very much a clinician first organization. And we show that in a lot of ways. One of which is we have an incredible customer success team that goes on site that, you know, goes to the elbow of these people. Because what people don't realize is that you're not just giving them a new technology, this is change management. They're going to change a little bit about the way that they practice and that's hard. That's scary to clinicians. Most of them are allergic to change, right? And so you can't just hand them a technology, even if it's the best technology, and say, hey, go use this, they'll push you away. Right. There's a great cartoon that I've seen and it was like a doctor pushing a wheelbarrow up a hill with square wheels and there's an inventor with the wheel, the actual circle wheel next to him and be like, hey, I have this great tool. And they're like, sorry, I'm too busy to look at that. Right. That's like clinicians when you come to like technology because they've been over promised and under delivered for so long that they don't inherently trust. And so the first thing is you have to work tirelessly with the clinicians. You have to build clinical champions. You have to build people willing to record a testimonial that they can share with the rest of their content in the organization. You have to have strong support from leadership like one of the through lines for these three organizations, Rush, McLeod and FMO. Amazing, amazing leadership team. The CMIOS, the CIOs, the TTOs, like they were fully invested, fully on board. It started at the top and it trickled down through the organization and you can't replicate that. Right. Like that's really hard. The other thing I think that sets, you know, Suki apart a little bit is that we never consider ourselves a vendor. And maybe this is a cheesy line, but like we genuinely partner with these health systems to be their AI partner for the next five years. Our goal was not to sell them an ambient scribe or ambient AI. That wasn't what we were ever building. We were always building an ambient AI assistant that would help them in all different types of administrative tasks. And so when we were pitching to them, it wasn't like, hey, here's our point solution, you should adopt it. It was, you're going to need AI partner that sits at the absolute like bleeding edge of tech and healthcare and we can be that partner with you. Starting with ambient AI, moving to Rev cycle, you know, assisted rev cycle, moving to clinical decision support and things like that, because that's where AI is going. And so I think we tried to paint a bigger vision than just sell them what they were looking for that day. And I think that helped get kind of buy in and belief that we weren't going to be just today's solution, we were going to be their partner as this kind of AI world explodes over the next five years.
- [10:17]
A
Mac, I want to turn this around a little bit too because again, Josh just spoke about the importance of that partnership piece. Right. From classes perspective, from your perspective, from a research perspective. Right. What questions should health systems be asking them? We should be asking partners that most of them aren't asking.
- [10:36]
C
You know, one of the things that hindsight is 2020 is one of my favorite phrases.
- [10:40]
B
Right.
- [10:40]
C
It's easy to look back and say, well, we should have done this or we could have done that. That's where I hope class comes in. Because we aggregate the real and then try to provide that back. And that's exactly what this ROI study is trying to do. Right. And our other research is to say, okay, this is what other teams have done. Here's the mistakes that may have been made or here's the missteps, let's say. And I think in good faith. But at the same time we also need to validate the positive. So a couple of just quick thoughts there. As you're assessing working with any organization or vendor, you need to look at them from a long term perspective. Are they a partner? And Josh, you talked about this earlier. We've seen this with Suki's data. People view Suki as a partner. There are other teams. Obviously this is a very crowded marketplace, so to speak. There's freemium solutions, there's other solutions from large organizations, etc. EHRs are introducing different technologies. And so as you're looking at the teams you're engaging with, you need to be looking at the long term play. Who is really articulating a clear roadmap, who has a beyond the note functionalities, who's kind of coming to you and saying, we're not just here for you today, we're here for you tomorrow and the future. And I think that that is something that a lot of teams are aware of, but it's hard to kind of filter that out. So ask hard questions, Ask the teams that you're engaging with. Where are you today? Great. We want to talk with a reference customer. We'll go to class or other sources and get our data. But where are you going? And make sure that you are aligned with that vision, because where the vendor wants to go may not be where you want to go or may not be as helpful for you. So I think that groundwork is. So that groundwork has to be developed so that as you move forward together, you have better outcomes and you have realistic timeframes for deliverables, things like that. One other quick thing I'll share, and Josh, you touched on this a little bit. I think it's absolutely essential, as well as you're looking at piloting a solution and scaling a solution, you've got to be really mindful of the milieu of the people that are part of that. Whether you're doing tranches of providers and different specialties, and you're going live with different groups, make sure it's a healthy mix of excited people, technophiles, early adopters, volunteers, people at risk of burnout, people not at risk of burnout, because that way you're going to get a really fair, holistic view of the actual impact of these tools as you pilot and then go to scale. So, and this is again, something we saw through this study, McLeod and others, they look really closely at that for their own process. And I can say that those are some best practices that will set you for success.
- [13:10]
B
Just wanted to touch on two of those things real quick. One, Mac, I think, you know, as you just mentioned, the who you choose kind of at each cohort of the organization is critically important. And I think McLeod would go so far as to tell you they chose wrong at the beginning. Right. Because they actually only wanted to give this to most efficient providers because they were the ones who kind of could earn it or whatever it was, right. Or that that's who they thought would adopt it. But what's really interesting is that they found that there's no silver bullet. There's no. There's no guarantee of who it'll work for and who it won't. It really is a kind of a personal preference. And so you don't want to be too specific about your. Your. Your core kind of test group. You want to make sure you're testing it all throughout the organization to make sure that you're kind of seeing the broader scope. The other thing that was interesting, Mac, that you were touching on is what is it that the company or the partner is doing today and what are they not? And I bring this up because one of kind of the ethos of Suki has been to be very humble and be very transparent because in tech, there's nothing worse than over promising and under delivering. And one of the things that I love about our founder is he'll go to a health system and say, hey, here's where we are today. Here's where we're not today, but here's where we're going. And I think that that's kind of a breath of fresh air because there's a lot of people today, hey, we have nursing figured out. I call bs. They don't. Nursing is so difficult and so different from ambient AI for clinicians, but everyone wants to say that they have it. We could say we have it, but we haven't gotten it all figured out. We're building it, we're partnering with teams, we're trying to get it to where it's as good as where it is for clinicians, but we won't over promise that. And I think that's really critical in this space right now because AI is going so fast, people will believe anything you tell them.
- [15:04]
A
And I just wanted to tag onto that too, because you both have talked about the partnership piece and I think again, as you've just said, because the space moves so fast, specifically around technology and AI, something that's true today might not be true again tomorrow.
- [15:19]
C
Right.
- [15:19]
A
So you need a partner, I feel like, that understands that and understands that it needs to move within the organization. Mac, you touched on that. It needs to be somebody that really knows, okay, this is how we're moving, which is so crucial. And Josh, I do want to spend just a little bit more time on some of these challenges. Right, You've touched on it just now. Some of the challenges that organizations may be facing that do really want to do this, they know this is beneficial. They know they need this. Right. They are doing it. What are some of those biggest operational and change management challenges that they should be prepared for right now?
- [15:51]
B
So I'm going to answer this in a little bit of a different way because what's interesting is I feel like almost everyone has tried it at this point. The problem is if you tried it two years ago, you might as well have not tried it because it's a completely different product. Right. And what I'm seeing is a lot of these health systems who tried it and it didn't take and it didn't work. Felt like, well, this isn't going to work for us. The truth of the matter is the product has gone and gotten so much better. Think about it in your personal life to two years ago, if I use ChatGPT, it was like for random things. Now I don't go a day without using ChatGPT or Claude or any of these things and they become a part of your like lifeblood, you need them. But it wasn't like that two years ago. The software wasn't good enough. Right. So yeah. Did it show some benefits? Absolutely. But it wasn't where it is today. So part of it is overcoming this bias of like, I tried it, it wasn't great. The other thing that I always try to be really clear is this is not a silver bullet. This isn't going to all of a sudden make your clinicians super happy regardless of everything else out there. I think if people believe that this is like the perfect tool, then they're disappointed. But if you say, hey, I can save you 30% of your time or I can let you go home on time at the end of the day and spend time with your family, that's more realistic. And then they'll start to build on it and they'll start to learn it and they'll to get more and more out of it. So I think being realistic about it is really important, getting buy in from the right people because oftentimes the biggest challenge. Right. And I think Mac talked About this with CFOs is that the first question is how are we going to pay for this? And if you go with how are we going to pay for this? You're thinking of it as a cost center. The truth of the matter is this is a revenue driver, but it's not framed as a revenue driver because it's a new technology. Every new technology is kind of thought of as a, as a cost. Right. But the truth is you almost can't not make money using, using ambient AI, whether it's in seeing more patients, saving more clinicians, you know, whatever, having, you know, better patient satisfaction scores, improving coding, there's a million ways to make money. And the software price has gone down so significantly over the last two years that like it should be a no brainer. But people still see the upfront cost, right. And so getting them over that. And one thing Suki did that I think was smart was we did utilization based pricing. So instead of charging for seat licenses like you get with a DMO and things like that, where it's hard because $200, $300, if you want to do that for the enterprise, nobody can afford that. We charge a very, very small amount on the upfront to turn the lights on. And then it's just you pay for what you use, right? So If A clinician works one day a week, they use it 20 times a month. It's not costing them very much. But if a clinician uses it every day, 30 times a day, it's cut, it's, it's capped at a certain number. So they're not spending a fortune either. So either way you're getting value out of it. And I think those are some of the ways you have to look at this and overcome the inherent challenges that are there. Yeah.
- [18:43]
A
Have the conversation. Right. Explain it to people, educate people, which is so crucial from a change management perspective. Mac and Josh, it's so fantastic to have you both on. What a great conversation. This is fantastic. Anything else you want to share that comes to mind that we haven't touched on? Anything else that you think might be important? Mac, I'll start off with you.
- [19:01]
C
Just the takeaway here is that again, and Josh has talked about this a couple of times and so appreciate surfacing this. Lucas, anyone who's listening, you've got to be looking closely. And I don't need to tell health systems this. Everybody's looking at their budgets, right? Everyone's looking at cost, framing this as a, as a positive net generation across a lot of different areas. Whether it's coding, uplift, whether it's again, patient, voluntary patient increase, visits, etc. Work RVUS dollar per, you know, dollars per clinician increase. Those are things that you need to be able to have and be armed with so that you can have those conversations as an organization with your CMIO C though, as a leadership team and implementation team to make sure that you are going into this eyes wide open, expecting what it can do and just as importantly what it can't. But then to be able to have that validation, I think that's really critical. The rush to me too, I've got to have this also is, is real. But doing it in a very deliberate way and looking at teams like Suki that have validated ROI to me is, is worth the time. Worth the time to review the report, worth the time to engage.
- [20:07]
B
Yeah.
- [20:07]
A
Josh, anything else to add here?
- [20:09]
B
Yeah, just quickly. I mean, I think look under the hood, right? Get under the hood of the company that you're partnering with. Because this is not a one year partnership or a two year partnership. This is the next five to 10 years. Right. Health systems are going to adopt AI in mass if they haven't already. I could bet all the money in the world that it will happen because it has to happen. It's the only thing that can potentially help alleviate the crisis that we have of, of doctor shortages. Right. And patient access. And so make sure that you're partnering with a company that has built an AI native product and isn't just bolting on additional tools that they can then sell. It's critical that the infrastructure of the company that you're partnering with is AI and it's built for the future as opposed to what's available today. That would just be my recommendation because, you know, everyone says the same thing. Everybody states, it's almost the same facts. It's impossible to stand out. But the companies that really do their due diligence and get under the hood and understand the AI, they're the ones who are going to be successful over the next few years.
- [21:11]
A
Josh and Mac, we certainly had round wheels on our wheelbarrow today. I don't feel like we have the square wheels on, so that's great. I want to thank you both again for your insights today. We also want to thank our podcast sponsor, Suki, for bringing us together for this conversation. So great to have them. You can tune into more podcasts from Becker's Healthcare by visiting our podcast page @becker's hospital review.com.