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.