Hi, everyone. This is Lucas Voss with Becker's Healthcare. Thanks so much for tuning in to the Becker's Healthcare podcast series. Very excited for this topic today. Very relevant in today's day and age. Beyond the does practical AI for medical device management. And joining me for today's discussion, so excited to have him, Steve Martin, chief technology officer at TriMedx. Steve, thanks so much for being here today. It's great to have you. Happy to be here. Thanks for having me.
Absolutely. For our audience that might not know you, could you just introduce yourself and just share a little bit about your work in health care? Yeah. You bet. So, Stephen Martin, chief technology officer at Traimetics, but, a long time in in in tech. I won't bore you with with with all the details, but, I really started my career
at the early days of Netscape. So going back to the, you know, the early days of the browser or the commercial Internet, I was at Microsoft for fifteen years, ran the, the Azure business as, as well as a few other things, and then, went to was at GE for a while before getting into health care. I in my late days at Microsoft, you know, I I had a really good piece of advice from a mentor.
They said, in reality, there's only three industries on the planet that matter for the survival of the species. There's water, there's energy, and there's health care. And at that moment, I I kinda took the pledge to say I'm gonna spend the rest of my career in one of those three areas, and the last five years has been exclusively in in health care. I worked at Change Healthcare before. I was at, UnitedHealth, ran big portions of, of of of Optum's IT infrastructure.
But the thing that people probably know the most about me was I was the person that ran the, the recovery after the Change Healthcare cyber attack at United and devoted, about a year of my life, to just getting things back, up and running after after the cyber attack, and then helping learn as much as we could from that and sharing with the industry.
Yeah. I'm so excited to have you because, again, you have such great perspectives on the landscape right now, but, also, again, as you've mentioned, sort of the early days of the commercial Internet. And I feel like we're experiencing sort of the same right now, with technology and health care specifically. There's a lot of noise around AI specifically in health care right now, the bright shiny objects that are popping up everywhere.
From your perspective, what's the right way for health systems right now to separate this hype that we're having, right, from practical innovation, and what should they consider when they're building an AI driven framework for their health care technology management? It's a great place to start. And if I was in the shoes of, you know, all of those, hardworking providers out there, it would be the question that's absolutely top of mind. How how do I get going? How
do I separate back from fiction? And and I think the first thing that you do on on any good assignment, right, is to is to understand how you can segment it just a bit. And so I I I I encourage everyone I talk to about this to to gravitate away from the first use case that we all talk about. The first use case in AI that comes up in health care all the time is, hey. Is this gonna replace a doctor? Mhmm. Are we going to put a bot in front of a patient and have that that
that bot do all of the work. And and and that that that is something that we could talk about on another on another show, and maybe there are some scenarios for handling service. But that is really not what we're talking about today. Yeah. And, in fact, for all of the the the the issues associated with that, there is so much that health care systems can do to implement AI that has nothing to do with patient immediate patient delivery.
And so I really encourage people to think about how could you, you know, use Leverage AI just to improve, you know, the the things that you're doing on a daily basis for supply chain, for making sure that your your hardware is up and running and is is absolutely optimal, For doing, workforce management in terms of load balancing, making sure you've got the right piece of equipment at the right time. There are tons and tons and tons of use cases that don't have anything to do with care delivery.
We should have the care delivery, conversation. We should have that that that debate. But in my mind, there is so much that we can do and learn, in the health care space with AI before we even get to, you know, the the the care delivery side of the house. And we're just starting that process, I feel like, to explore all of those areas that are useful, that we can really see a difference and the difference that AI can make. Absolutely.
When we're looking at the application, though, what are some of the metrics, and what are some of the things that leaders should look at when they are evaluating whether AI is is really delivering real value for their organization, specifically in health care technology management? What are some of those metrics that that you would say, hey. We need to look at them? Yeah. You bet. And the the the macro level thing that I would say is, one, be prepared to experiment,
and try different things. And if you assuming you've got an an organization that's large enough to support the the IT development of of these kinds of things, you should iterate very, very quickly or partner with organizations that that that are and we should come back to that in a in a in a second. But I think the the high order bid is experiment quickly and and not just because it's it's the right way to approach the problem, but also because in this space, you should expect very quick ROI.
In fact, the thing that I tell people over and over again, this is not like the other systems that you install where you wait, you know, months and potentially even years, to to to start seeing ROI on those those types of investments. The impact for this work in the AI space should be relatively immediate. And if it's not, then continue to experiment, continue to iterate. But this is a place where you get to give some very different, advice than we have historically when it comes to technology.
Expect results very quickly. Mhmm. And if you're not getting them, listen, because that is that's telling you something because it it it should be there. Otherwise, there's plenty other things to continue to iterate upon. So the return of investment, just to come back to this, the ROI is really the most critical thing for leaders to look at from from an organizational standpoint. Doesn't necessarily automatically mean it's it's it's, it's it's dollars gained,
but it could be cost avoidance. Right? So we spend a lot of time talking about cost avoidance. It's also in making sure, you know, hey. The patients that you serve over the course of a week, what was that? Was that was that an optimal experience? Did you have all of the staff that you needed when you needed them, to make sure that your delivery was exactly what you what you wanted and reflected the philosophy of your of your organization.
And the cost management side is just as important as the as the revenue maximization side. Yeah. Absolutely. I feel like you, more than anybody, knows about risk and knows about how to manage risk and be safe and promoting safety across an organization. And I was doing some research for this podcast, and there's 80% of health systems there using AI internally. It's there, but only 17% of them have a mature governance structure, which I think is very, very interesting.
How do health systems ensure AI supports compliance, right, risk management rather than, okay, here's this new system, and they're introducing new vulnerabilities that they might not know about. How can they do that? Yeah. And and anytime we have a a an area of rapid change of technology, your point is exactly right, and you and you and you have to pay attention.
It does get back to the other part of the the conversation from your your your prior question, though, because, well, Ed, to your point, yeah, the 80% of health systems report using AI internally. That's largely a number derived by what they're doing. Are they bringing AI to the table?
I think that it would be it may surprise some health systems to find out that that number is probably closer to a 100% because the partners that you work with, the software that you, employ, that all the technology that you license, those suppliers are using AI. So you may be using AI as a function of using that technology whether you know it or not. And so this gets you know, it's even more to your point about how critical the
governance part of this is. Governance is key, and you have to own it. You have to own it. No vendor is going to be that role provide that role for you. You have to take a leading role on acceptable use, and you have to go in and ask the hard questions. And if the people that you're working with are not coming to you saying, here's what we're doing on acceptable use. Here's our internal board for how we govern
AI. Here's how we think about the responsibility that we have in in using these to make sure that we don't have, you know, issues around discrimination or or or or or over variability. Like, those kinds of issues come in. Here's what we're doing about it. If your suppliers and vendors are not having that conversation with you, that is a warning sign, because you you you've gotta go and ask
those questions. Because if if they're not driving it and coming to the table telling you about it, that may not be as mature as you want. And that's another sign that you've gotta play that play that role for the for the governance of it. Yeah. And I wanna stay on this a little bit too because, again, everything is moving so fast, and it's certainly affecting
organizations. And I'd love to know what your perspective is on how AI is going to evolve specifically in health care technology management right over the next three to five years. How do you see the role of AI changing in that regard? And I'd also love to know what what you're working on to to really support that long term innovation for organizations. Yeah. I I'm and I I if those that know me know that I I'm neither a pessimist nor an optimist. I I I'm not a half full, half empty kinda guy.
I'm just it's just half. Right? It's just half. There's no reason to describe it as one way or or the other. But but, actually, against the trend, this is a place where I tend to be pretty optimistic. Like, there's a ton of naysayers, and and and the responsible use in AI conversation is a is a critical one. But I tend to think that this technology at the end of the day is going to help us deliver the right people in their at the right moment with the right equipment, work in the
right way. And that is really the holy grail for health care. Think about how long you wait to get an appointment. Think about how long you wait when you're there. Think about all the paperwork that hospital administrators, doctors, nurses, other caregivers have to do for for procedural things.
If we can together ensure that we're putting our providers in a way to spend the vast majority of their time in front of patients and AI as a secret sauce for helping make that happen, I think we've really accomplished something. And once we've done that, then we have earned the right to have that second conversation about how it can help drive a better outcome for patients after we've
gotten through that first point. But in my mind, AI has permission, to enter this chat, if you will, with regards to doing optimization work in health care. And it needs to show us that it can deliver on all of those things for us to have the second conversation on the delivery side. Yeah. Absolutely. Is there anything that excites you that you're working on right now that you're really optimistic about that that you really love that you can you can bring
to organizations? What are you working on that that's really innovative that you think is is really going to make a difference? You bet. Well, first, I would just start by saying we're doing the small things right. We've, you know, we've got the governance body. We're we're we're we're having on behalf of our our customers. But I what AI is allowing us to do is to have a set of conversations with customers that previously were really tough.
For example, there are health care, providers and and and and and large organizations, the health care space, that have a philosophy about, I wanna make sure that the hardware that's needed, the equipment that's needed for any patient is available in that room 100% of of the time. That's their philosophy. That's how they wanna operate. We have other hospital systems that tell us there is no way that's an affordable option
for us. We need to make sure that the right piece of equipment is available at the right time, but I can't afford to have not one more piece of equipment in this hospital than than I am. And you talk about the the the issues facing rural hospitals right now and care deliver care delivery in those spaces. Nothing is more important than the cost optimization side because it it'll determine whether or not they're allowed to continue to to provide health care or not, which is which is critical.
We can use AI to have that conversation with those health care organizations. What is your philosophy on how you wanna operate? Is it just in time based on financial constraints, or is it everything in every single case? And we can use our technology then to make sure that is what you have. And so I think the most exciting bit about this really is making sure that technology is being used to better reflect the philosophy of the organization in terms of how they want to operate in a maximal in a
maximal way. And watching people just light up to say, hey. How am I gonna use AI? And then I get to say, what kind of care do you want to deliver? What is important to you about your patient experience? And not just the pie in the sky
stuff. Like, let's get down to the brass tacks about, you know, what a day in the life looks like, what your affordability is, you know, what are the what do those deals look like, and how can we help you with technology make that absolutely real on a day in and day out basis and do that without it being overbearing? Could it just be present? Could it just happen, without you having to do a lot of things different than you have in the historically?
Yeah. We're coming full circle. Right? That's how we're eliminating the noise. That's how we're separating the bright shiny objects for the things that are actually making a difference, which is key. Steve, it's so great to have you. Thanks so much for taking some time with us. We've certainly entered the chat for this one. I'd love to open the floor to you. Is there anything else that that you wanna share that that we haven't touched on that
might be important for our audience? I I would just say make sure you're taking an expansive view. You're working with technology providers that are having the hard conversations. They're thinking about cyber. They're thinking about responsible use. And making sure that when you go down this path,
you you may not know the answer. If you do a good job of the data, analytics and you really get into the the guts of the AI of what the art of the possible, the questions of today versus the answers of tomorrow, those could be two different things. And so this is a place where we get to allow some manifest destiny. Right? Some some opportunity to learn things that we didn't know were out there and just get smarter day in, day out. It's an exciting time.
And I think if we're done right, this will bring out the best in all of us. Steve, thanks again for being here. Great insights. Thank you. Thank you. We also want to thank our podcast sponsor, TriMedx. You can tune in to more podcasts from Becker's Healthcare by visiting our podcast page at beckershospitalreview.com.