← Becker’s Healthcare Podcast
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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. Very excited for this topic today. Very relevant in today's day and age. Beyond the buzz, 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 was great to have you.
- [00:22]
B
Happy to be here. Thanks for having me.
- [00:24]
A
Absolutely. For our audience that might not know you, could you just introduce yourself and just share a little bit about your work in healthcare?
- [00:30]
B
Yeah, you bet. So, Stephen Martin, Chief Technology Officer at Trimetics, but a long time in tech. Won't bore you with all the details, but really started my career at the early days of Netscape. So going back to the early days of the browser or the commercial Internet, I was at Microsoft for 15 years, ran the Azure business as well as a few other things, and then was at GE for a while before getting into healthcare in my late days at Microsoft. Really good piece of advice from a mentor. He 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 healthcare. And at that moment I kind of took the pledge to say I'm going to spend the rest of my career in one of those three areas. In the last five years has been exclusively in health care. I worked at Change Healthcare before I was at UnitedHealth, ran big portions of Optum's IT infrastructure. But the thing that people probably know the most about me was I was the person that ran 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 the cyber attack and then helping learn as much as we could from that and sharing with the industry.
- [01:56]
A
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 healthcare specifically. There is a lot of noise around AI specifically in healthcare 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 healthcare technology management?
- [02:34]
B
It's a great place to start and If I was in the shoes of all of those hard working providers out there, it would be the question that's absolutely top of mind. How do I get going? How do I separate fact from fiction? And I think the first thing that you do on any good assignment is to understand how you can segment it just a bit. And so I encourage everyone I talk to about this to gravitate away from the first use case that we all talk about. The first use case in AI that comes up in healthcare all the time is hey, is this going to replace a doctor? Are we going to put a bot in front of a patient and have that bot do all of the work? That is something that we could talk about on another show and maybe there are some scenarios for handling, but that is really not what we're talking about today. And in fact, for all of the issues associated with that, there is so much that healthcare systems can do to, 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 use leverage AI just improve the things that you're doing on a daily basis for supply chain, for making sure that your hardware is up and running and 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 healthcare space with AI before we even get to, you know, the, the, the care delivery side of the house.
- [04:19]
A
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 really delivering real value for their organization? Specifically in healthcare technology management, what are some of those metrics that you would say, hey, we need to look at them?
- [04:46]
B
Yeah, you bet. And the macro level thing that I would say is one, be prepared to experiment and try different things. And assuming you've got an organization that's large enough to support the IT development of these kinds of things, you should iterate very, very quick, are partner with organizations that are, and we should come back to that in a second. But I think the high Order bit is experiment quickly. And not just because 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 months and potentially even years to start seeing ROI on those types of investments. The impact for this work in the AI space 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. And if you're not getting them, listen, because that is, that's telling you something, because it, it should be there. Otherwise there's plenty other things to continue to iterate upon.
- [05:59]
A
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 an organizational standpoint.
- [06:08]
B
Absolutely. And ROI doesn't necessarily automatically mean 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, hey, the patients that you serve over the course of a week, was that an optimal experience? Did you have all of the staff that you needed when you need them to make sure that your delivery was exactly what you wanted and reflected the philosophy of your, of your organization? And the cost management side is just as important as the revenue maximization side?
- [06:43]
A
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, they're 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.
- [07:20]
B
And anytime we have an area of rapid change of technology. Your point is exactly right. And you have to pay attention. It does get back to the other part of the conversation from your prior question though, because. Well, to your point, ye 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 may surprise some health systems to find out that that number is probably closer to 100% because the partners that you work with, the software that you employ, 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 using these to make sure that we don't have, you know, issues around discrimination 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've got to go and ask those questions. Because 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 got to play that role for the governance of it.
- [09:04]
A
Yeah, and I want to 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 healthcare 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 you're working on to really support that long term innovation for organizations.
- [09:31]
B
Yeah, if those that know me know that I'm neither a pessimist nor an optimist. I'm not a half full, half empty kind of guy. I'm just, it's just half. Right, it's just half. There's no reason to describe it as one way or the other, but actually against the trend, this is a place where I tend to be pretty optimistic. Like there's a ton of naysayers and the responsible use in AI conversation 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 the, 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 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 is a secret sauce for helping make that happen, I think we've really accomplish 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 healthcare. 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.
- [10:59]
A
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?
- [11:11]
B
You bet. Well, first I would just start by saying we're doing the small things, right? We, you know, we've got the governance body, we're, we're having the conversations about responsible use. We're doing that on, on, on, on behalf of our, our customers. But 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 healthcare providers in large organizations, the healthcare space, that have a philosophy about, I want to make sure that the hardware that's needed, the equipment that's needed for any patient is available in that room 100% of the time. That's their philosophy. That's how they want to operate. We have other hospital systems that tell us there is no way that's an affordable option for, 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 I am. And you talk about the issues facing rural hospitals right now and care delivery in those spaces. Nothing is more important than the cost optimization side because it'll determine whether or not they're allowed to continue to provide healthcare or not, which is critical. We can use AI to have that conversation with those healthcare organizations. What is your philosophy on how you want to 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 going to 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 what a day in the life looks like, what your affordability is, 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?
- [13:29]
A
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 you want to share that we haven't touched on that might be important for our audience?
- [13:50]
B
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 may not know the answer. If you do a good job of the data analytics and you really get into the guts of the AI, of what? The art of the possible, the questions of today versus the answers to tomorrow. Those could be two different things. And so this is a place where we get to allow some manifest destiny. Right. 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 diff done right, this will bring out the best in all of us.
- [14:33]
A
Steve, thanks again for being here. Great insights. Thank you.
- [14:36]
B
Thank you.
- [14:37]
A
We also want to thank our podcast sponsor, trimedx. You can tune into more podcasts from Becker's Healthcare by visiting our podcast page@beckershospitalreview.com.