Hi, everyone. This is Brian Zimmerman with Becker's
Healthcare. Thank you so much for tuning in
to the Becker's Healthcare podcast series.
Today, we're on-site at Becker's thirty first annual
meeting, the business and operations of ASCs,
and we're going to discuss predictive scheduling and
the future of AI in health care. Joining
me for this conversation
is Waleed Nasr, cofounder and CEO of Medley.
Thanks for having me. Great to see you
again, Waleed.
Let's get in here in into the conversation
with an introduction. Just, you know, give us
some details about your your background and and
the work you're doing now. Yep. Medley started
as a marketplace that connected health care professionals
with facilities that needed short term, staffing.
And since then, we've evolved into a workforce
optimization platform and orchestration platform that centralizes both
core staff, full time staff, and flexible labor
into one platform. And then applying AI and
ML to be able to optimize
that staffing across your facilities
and,
increasing
retention and also increasing patient throughput. Yeah. It
it's cool to hear about how how you've
evolved over over the years in the AI
component. Right? I mean, let's get right after
it because, of course, that's what everyone's talking
about probably for the for the last couple
of years now and, into the foreseeable future.
But,
the the stat I have here is nearly
half of medical practices in The US have
been using AI to work at work for
over a year. So from your perspective, where
has AI made the biggest impact so far?
And how have you seen it evolve just
at I mean, it's clearly we're we're past
the state of just pure hype. People are
using this technology now. So,
from your POV, where are we at? Yeah.
That's it's it's it's definitely not hype,
but it definitely has to have a well
thought out applications. I think two of them
from our perspective is
medical scribing, where I think it's provided an
unlock for doctors being able to just not,
you know, have a natural conversation with their
patients and have that data go right into
the EHR system or EMR system. I think
that's been a very interesting application.
Another one, of course, is, medical coding, and
it's been, a great unlock being able to,
you know, be able to get, this information
to insurers much faster to get payment.
And those feel like really good applications
for AI as it is today with, natural
language. But we're we're really excited about is,
workforce orchestration.
And that is the intersection of machine learning
and AI,
and being able to orchestrate your workforce both
full time and, flexible labor under one, platform,
being able to, scheduling credentialing,
cross training opportunities. So you can amplify that
workforce from, internally before you even ever
you put a job out to an agency.
And I think that's a really interesting unlock
for the future of AI. And can you
talk a little bit too about just how
workforce orchestration is the the phrase you used?
Because why has that not been possible
until now, until with this kind of technology?
Can that's the way I'll phrase the question.
Yeah. I think it's a intersection of two
technologies. One, you have to have a platform
to be able to do that. And that
platform
has to has to have, multiple features that
that's like scheduling a credentialing,
full pool management, on call management. You know,
you gotta have integrations with EHR systems,
with HR systems. So it's the aggregator of
that data
and then the application of machine learning and
AI to be able to actually orchestrate
that staff according to that. And I think
that has been possible because,
while you, you know, you have just a
lot of point solutions, but you don't have
true platforms with AI to be able to
to provide that service. And and staffing and
health care is inherently
complicated. Right? Probably more so it's fair to
say more so than most other industries. I
would agree because,
you just have different work preferences for health
care professionals. You have credentialing. You have Right.
Learning modules. You have, you know, you have,
each unit in the hospital operates very differently
from each other. The OR schedules are very
different from infusion,
scheduling,
which is different from,
ICU. And so it's just it's not a
one size fits all, and, you have to
have a platform that can accommodate each setting.
Yep. Well, let's
get into, I guess because I know
many leaders across different types of health care
organizations are turning to this technology to, you
know, reduce
administrative burden, workload burden.
When you talk about managing the workforce, what
kind of metrics should folks be tracking out
there to see if, like, hey. This technology
is yielding the efficiencies that we're we're looking
for. Yeah. Traditional staffing is actually very reactive.
Right? And so they lack the data. If
you think about ASCs, they have distributed ASC
groups, you know, in different states. And,
I think,
the first thing you have to do is
centralize that data and be able to react
on it. And so right today is everything
is even from
large hospital,
systems to an ASC is is just very
reactive.
And so the first thing you have to
do is have a platform where you can,
centralize all that, and then you're able to
apply those, that that AI and be able
to have things like, tuning overtime,
fill rates, workforce sentiment. Right? That's a big
one because if you understand your workforce, are
they gonna churn? When are they gonna churn?
And you could start to predict these things
so you can start to get ahead, and
you're not reacting to using
agency as your first choice.
And I think that's a very important part
of some of those key metrics. What's interesting
though is each department in these facilities
have different metrics that they're looking at. Like,
the finance team is looking at different metrics
than the CNO or, the schedulers. And so,
again, having a platform that could, disseminate that
part that right information to the right person
really makes it more proactive than reactive. Mhmm.
And and can you share a little bit
about, so thinking about this from the ASC
perspective specifically,
of course, it's it's kind of known that,
especially for independent ASCs, they don't have necessarily
the same kind of resources
as as hospitals or health systems. That said,
their their ability to to bring in staff
has often been about the experience. Right? The
experience that they can offer staff. It seems
like this kind of technology is very much
in keeping with that. And if for for
ASCs to continue to offer those folks that
kind of experience, this is something that they
should be really thinking about. Definitely. I think,
what in a what ASCs need to understand
is well, first of all, this technology
can be applied at the ASC level as
well as all the way up to, the
hospital and and and system level. And so
I think what's important is for ASCs to,
embrace
the flexible labor model. Right? And by doing
that, it'll really give those, the the the
ability to bring in this new workforce and
then provide them the experience. They you know,
this workforce is very interested in the flexibility,
but also the flexibility
of, being able to work in different settings.
You know, being able to cross train and
have someone work at PACU and pre op
is interesting to them because that's what they're
looking for, like you said, experiences.
Mhmm. And and then I'll
I'll I'll phrase this question to you then.
For folks out there who are maybe thinking
about doing this
in the early stages of trying to implement
this technology,
what advice do you have for for those
folks trying to bring AI into to their
workforce management? I think
start small.
Right? Start with scheduling and credential. A lot
of this is happening in spreadsheets or in
filing cabinets. And so those
are repetitive
processes
that is easily automated. So I would start
with that. I would map out your your
your processes on paper, and then I would,
look for a platform
that can scale with you, start small that
starts small and then allows you to scale,
much more broadly in the future when when
you need to. Yeah.
Anything else to add before we let you
go? Any final final thoughts, something to reemphasize,
or maybe something you didn't get to say?
No. I think we're at a exciting,
intersection in health care where both
platforms and AI can really help amplify the
workforce,
can help these facilities retain their current workforce,
and most importantly,
can,
provide
the, ability for their core services to be
profitable while providing value based care at the
same time. So I think platforms and AI
can definitely work to provide that service. Yeah.
Well, Wally, thank you so much for for
taking the time. It's a pleasure to speak
with you again. Thank you for having me.
We also wanna thank our podcast sponsor, Medley.
You can tune to more podcasts from Becker's
Healthcare by visiting our podcast page at beckershospitalreview.com.