Hello, everyone, and thank you for tuning in
into the Becker health care podcast series. Today,
I am pleased to be joined Barr as
we focus on payers and some of the
administrative challenges they are facing in light of
Cms
regulations, pertaining to Medicare Advantage, including compliance with
state and federal prior authorization, requirements, and interoperability
and increasing transparency and accountability
reporting.
These changes are accelerating the need for health
health plan payers to accelerate, optimize and automate
many administrative functions would some estimate to make
up 25 percent of the 4700000000000.0
total health spending in the Us.
Before I begin, I'm going to introduce today's
speaker, Paul, Senior industry practice director of view
uipath.
Uipath is a enterprise scale intelligent automation platform.
That combines Id, Rpa, process mining, task mining,
process,
orchestration, and Ai ml based capabilities
including communications mining for Nlp and unstructured data
processing.
Uipath customers appreciate the scalability,
flexibility of the solution, along with ease of
use in configuring and training ml models. Paul,
thank you so much for joining us today.
How are you? Thanks for happy me, Terrific.
Yeah. Wonderful. What's 2 gonna started. I first
wanna thank you again for joining the podcast.
He's also a bit more about yourself and
a little more about you uipath.
Sure.
So I've actually had the privilege of serving
in the health care industry now for upwards
of 35 years. And I've had the opportunity
to really traverse
the various sectors. I started in medical education,
jumped over into medical
information systems.
And then got into disease management,
jumped over then into consulting where I spent
the better part of 14 years with a
big 4 firm, consulting to the various sectors
of health care. And by that, I mean,
bio pharma,
payers and providers really working with them to
optimize their business.
And then spent the last 6 years really
up these this intersection of High tech and
healthcare care with some of the hyper dealers
leading
industry strategy for companies like Google, and Amazon
Aws.
In terms of Uipath, and thank you for
the the kind remarks in the intro,
Uipath really is is a platform for innovation
and automation. And within healthcare, we see so
many point solutions that exist and there's a
lot terrific innovation going on. But a lot
of the customers that I speak with day
in and day out, and it's a big
part of my role is really to beat
with executives of payers specifically. And
our responsibilities
overseeing payers and providers in the Americas. Is
really to meet with executives and understand what's
on their mind relative to their strategic
transformation initiatives. A lot of business processes have
been digitized, but we're capturing information, but we're
really not able to unlock
the value that's contained within that information. So
Uipath as a platform really serves as a
unification capability
that kind of meets customers where they are,
can tap into the source systems they have
and then begin to introduce
automation, intelligent automation and some of the more
advanced technologies, large language models, etcetera
on the data so that it can be
freed and used in in meaningful ways. And
we're finding this is really particularly relevant and
applicable with a lot of the regulations that
have both been published in our fourth coming
from Cms and others just in terms of
the challenges that payers have, and the need
to really move faster
in a safe and effective way leverage the
technology in the right place at the right
time, but then also do so in an
explain in an accountable way, and we've got
some ways that we've been thinking about that.
That's a little bit about Uipath.
Yeah. Yeah. Wonderful. Thank you so much for
giving us that explanation. So what are the
major trends you are currently seeing and how
are you helping our customers?
Sure.
So there's really 5 domains that we find
ourselves
talking with our customers about. And and we
assist in different ways. Again, we're about meeting
customers where they are and
really being
scaffolding, if you will to stripe across the
different systems. But medical cost management
is a is a large area
that we focus on. We're helping customers and
everything from care pathway
optimization to disease and
care management.
Programs.
The area we've really seen a lot of
emphasis recently is in the operational cost management
side of things. And these our areas having
to do with higher
authorization. There's been a lot of discussion around
that, particularly with the Cms
0057
dash f.
Regulation coming down
and the adaptations needed to comply with that
by 20 27.
Looking at high dollar claims is another area,
really the audit aspect of claims and cost
recovery. And we've got examples where we've helped
customers recuperate tens of millions
in over payments,
in instances where they've been able to go
back and and do the reviews, using
automation and using machine learning and an Ai
to start to look at,
those. And then looking at provider credentialing, you
know, keeping the records up to date, there's
a lot of paper involved, typically. The average
provider will have anywhere between 3 and 5
pieces of paper that get filed every year
that have to be
absorbed somehow. A lot of them aren't doing
it online, but there's still a remarkable amount
of business that still gets conducted via effects.
And we see this also in both prior
authorization and in claims where the information that's
coming in is is digital, but it's digital
Pdf documents or or fax documents
that they have to be ingested. They have
to be understood,
routed appropriately and then ad educated.
And then the last area that we've seen
quite a bit of progress is in more
of the fixed cost aspect, more technical and
that is in the automation of testing.
Uipath has some part of its platform,
testing capabilities, and we've seen upwards of 5
x increase in throughput.
By taking advantage of of the automated
script writing and testing capabilities that are part
of our platform. So that's kind of the
automation aspect of operational cost management.
The 3 remaining areas, member engagement tends to
be a very big area, and this is
around,
eligibility checks, personalized
communications and recommendations
the provider experience, and there's a lot of
talk in the industry about the ab operation,
and we're doing some work around intake and
correspondence
and
the referral networks and and working with our
payer customers and our provider customers to more
efficiently share
information as joint stakeholders in the care
of, of a member slash patient. And then
finally, you know, the area of around quality
risk and compliance And again, top of mind,
particularly in light of some of the regulations
that have come down. But assisting customers really,
again, getting back to
understanding the data they have the analytics against
that, and then being able to take actions
on those insights that are generated
and really start to look at ways from
which they can improve their business not only
from compliance perspective, but then also start to
mine that data to better understand their member
population where the risks may be
present and how they may be making adjustments
not only to their current business, but then
also looking for opportunities to introduce new products
and services that are gonna add more value
to their end member and be more competitive
ultimately in the market.
Wonderful. Thank you so much for giving us
that explanation.
So with Ai
occupying the majority of recent headlines and new
advancements seemingly announced it every day,
as I'm sure you know. How are you
helping customers transform their operations with automation that
includes Ml, a, and L m at scale?
Sure.
Well, there's a lot of experimentation that's going
on. You know, we're coming up. This November
will be the 2 year mark when open
Ai shook the world with its announcement.
And and really democrat
large language models to the to the general
public.
There since then, there's been a lot of
experimentation But we're finding that upwards of 70
percent of the pilots that are undertaken
fail. And it's not for great work that's
being done. A lot of it has to
do with the need for training. We just
announced a study. We did a global knowledge
worker study
we announced those results this this preceding Monday,
the eleventh of June.
And that, it found upwards of 85 percent
of those surveyed
were not given
structured training, particularly related to,
the use of large language models in their
business
and then also looking at Ai, Ml, large
language models in combination with automation.
So there's there's a big gap there, and
that's 1 of the learnings that that we've
seen is that while the technology is interesting,
there's definitely a right place and and our
right time for it.
In terms of what Uipath, we spent, since
2005 when we are founded,
we've been looking very deeply at at Ai
and n ml. And as part of our
platform, you know, there is certainly a number
of different capabilities as was mentioned around the
understanding of information and the context
but there's something that we've built into it,
which is key for regulated
industries like health and financial services, and that
is an Ai trust layer.
And what that really allows our customers to
do is establish the guard rails and the
mechanisms to explain
to report,
offer transparency over what these models are actually
doing with respect to their their data.
We're finding some some great use cases around
the,
what we call context branding as a part
of this. And that is the model is
pointed very
specifically
at a finite corpus of data that is
approved by the customer.
And,
by doing so, it reduces a lot of
noise. It gives you great guard rails around
and great explain ability in terms of the
answers.
In terms of another aspect of how we're
working with customers is guard there has not
been a lot of thought
given to process from the standpoint of a
combination of human plus digital worker.
You think about how businesses have evolved since
the fifties, really it's been
designed
hierarchical
around the capabilities and in some cases limit
limitations of human workforce. And what we're finding
is that as important as the technology is,
there's also a change management component
that's that's
also needed to be looked at as part
of any kind of transformation. And part of
what we have intrinsic to our platform is
the really the ability to look at a
process digitally.
And in the old days, you would typically
commission a study and you would you would
model out
what a process might look like. This is
a way to do that basically a way
to instrument a process automatically where we were
point an agent at a particular process.
Allow that process to be,
worked
across a wide
disparity of workers that are that are performing
that task, And then from that, using analytics
derive what the optimal pathway might be. And
then from that, we're able to then optimize
a process.
Some cases taking things that took days and
sometimes weeks and bring that down to minutes
because we've understood really precisely what's being done
why it's being done and then started to
look at those tasks that are optimally suited
for the human, like decision, like reasoning, and
those things that are more done by
automations, you know, things like
deter
logic where there are particular rules and and
other
mechanisms in place where you can
look at facts and data and then derive
and and output.
All of these things though
really result in, the need for what we
call human and the loop And there is
a desire in healthcare care to try to
automate as much as possible, but what we're
finding
is that by having a human in the
loop, it actually accomplishes 2 things at once.
The first is as you're bringing in your
process experts, the humans that have done the
work
and starting to introduce
automations that optimize, we're able to get that
expert insight and you're able to cod that
expert insight in a way where
essentially, the machines are ticking away a lot
of the the dr or the
from from that process. And then allowing
the knowledge worker or human to focus on
those things that are higher order value,
focusing on the member experience, focusing on truly
those things that are strategically important to the
business versus those things that are just simply
time consuming and moving data from 1 place
to another. So we're finding that when having
a human in the loop, we use machines
for what they're really prayed at, which is
repeatable,
dependable processes, safe and effective, and then humans
for the reasoning and the creative aspects in
which
add a lot of value to the overall
experience.
And then I mentioned before that the trust
framework that makes
makes part of it. And part of that,
of course is the interoperability
across 4 systems. The nice thing about Ui
uipath is we are easily
able to work with all the core systems
from
the the source systems that you may have,
the systems of records would to speak. And,
either by
Api
or fire interfaces or
even reading the screens. We we have
a number of patents in our portfolio that
are all about document understanding, natural language processing
and, you know, the ability to truly read
what's on a screen and understand what's happening
at that level of granularity.
And that offers really again, our customers to
back to the Guard rails conversation, be able
to start to use these automation capabilities and
intelligence capabilities
really holistically at the enterprise level a way
that's very transparent and scalable.
Yeah. Yeah. Thank you so much for giving
us all of that information. Paul, before I
let you go. The last thing I really
wanted to ask you is,
If you have any advice for our listeners
who are seeking to transform
and optimize how they operate with Ai led
automation.
Sure.
And you know, there there's always this natural
tendency when there's new technology. You know, first
and foremost, you know, even though there's a
lot of talk about Ai, large language models
and so forth, it's it's a part of
a larger solution.
In terms of, the other elements that you
need to take action on on insight. So
what we like to advise our customers
as we're working with them is really focus
on the right problems. Those those instead of
thinking particular use cases
and and the industry right now is, I
don't wanna say littered, but there's a lot
of standalone use cases out there, But they
don't really connect anything. So we encourage our
customers to really think more from a systems
perspective. What does the end to end process
look like? Anything And then how can we
look at that process in each sub component
of that process? And where is it best
work to add
automation?
Intelligent automation and the the different tools that
are available through the platform. And then where
is it best for having a human actually
take care of that work.
The other is there's also a rush we've
seen to just simply automate what you have
in current state. And
we're seeing really a resurgence and kind of
this back to basics, and that is let's
let's be excellent at doing simple things well.
And it's everything from receiving information from our
provider, processing claim, etcetera. But really
simplify and streamline the process as much as
possible before you really start to go down
that path of trying to automate it,
and orchestrated at an enterprise.
And that know, certainly the right tools at
the right time for the right problem. Gen
ai is a tool. Large language models are
a tool, Ai and Ml. They've been around
for a while. There are tools. Keyword search
is a tool in These tools are effective
in in particular cases. So it really requires
a a thought process to be very critical
thinking critically about the process asking of why
questions around the process. Why is it this
way? Is there perhaps a different way or
a better way to go about accomplishing something.
And that leads kind of going more into
an engineering principle of engineering concept around first
principles, and that is really break down the
processes
into small digestible components.
And and again, be critical and ask yourself
the question if knowing what I know today,
the technology I have access to the people
in the training and where they are right
now and the other systems that I have,
what might be the right way to go
about, transforming this process. And we're finding as
customers really start to take a step back
and think about things more holistically. They're able
to really
achieve excellent results in terms of simplification and
then
acceleration. It's kind of
inverse that people typically have gone about this.
And that is they automate quickly to try
to, achieve an Roi.
And, unfortunately, it it it may work, but
as I said before, a lot of cases
it doesn't. You know, this is a way
to spend 2 thirds of your time really
looking at the process and and breaking it
down and then 1 third applying the technology.
You know, the last bit I would say,
is don't forget about change management. This is
particularly now as much about
the knowledge worker and the knowledge worker experience
as it is the technology. You know, the
tech is moving very quickly, and there's a
lot of overload fatigue I would say, amongst
customers where they're... There's a new innovation or
a new way of doing something literally announced
every day. But Again, kind of taking a
step back, thinking critically about the process and
the outcome, the business outcome you're trying to
achieve, then also think about the people involved
in the change management and the education,
people are a little and you read the
surveys and the literature suggests that generally
knowledge workers a little nervous right now because
they they don't quite understand where they fit
in what these new automated systems might look
like. The good news is it's gonna definitely
super charge, and we like to use that
word, super charge their ability to add value
to the business and value to the members
while also taking those things that are low
value or repeatable
things that could be coded and take that
off their plates that can think strategically and
creatively. And and reason in ways that perhaps
they haven't had time to do before. And
when it's brought about in that way and
education has provided We find that there's greater
acceptance and greater
participation frankly as these programs are are rolled
out within the enterprise.
So there'll be some takeaways there that that
I would suggest, our listeners think about.
Yeah. Yeah. Absolutely.
Well, Paul, that is all the time we
have. For today. So on behalf of Becker
health care. I wanna thank you very much
for your time and thought provoking discussion today.
We also wanna thank our podcast sponsor, you
uipath. For further information about Uipath, go to
uipath dot com or contact paul at the
address provided in the show notes. You can
tune into more podcast from Becca healthcare care
by visiting our podcast page at becker review
dot com slash podcast.