Hi, everyone. This is Brian Zimmerman with Becker's
Healthcare. Thank you so much for tuning in
to the Becker's Healthcare podcast.
Today, we're on-site at Becker's payer roundtable. We're
going to talk about the future of member
experience, engagement, efficiency, and outcomes.
Joining me for today's discussion is Sadie Rizzuto,
vice president at enterprise technology solution implementation with
Humana, and Stuart Langley, senior vice president of
client services with Evervise.
Sadie and Stuart, thank you so much for
being here. To begin, I'm gonna tap on
each of you to introduce yourselves and share
a few pertinent details about your your your
professional background and your organization.
Stuart, why don't you kick things off?
Sure. So my name's Stuart Langley.
I am SVP of client services at EverRise.
And,
EverRise, we are a a full services BPO
providing contact center,
back office, and technology services.
And we have a specialism in the health
care space working with wonderful clients such as
Humana. Excellent. Well, with that, that's a perfect
transition over to Sadie then.
Sadie Rizzuto, vice president for technology enablement and
readiness within our insurance operation space at Humana.
Within Humana, we focus on our Medicare and
Medicaid
population and how we improve our health outcomes
within those members.
I am responsible for several product teams, including
our enterprise CRM and knowledge management populations, and
I'm also responsible
for our,
artificial intelligence,
program for insurance operations.
Excellent. And and, Sadie, we could begin with
you with this next question.
So,
when we think about predictive models and and
leveraging those to deeper deepen member engagement, you
know, it's not just about sending more messages,
but driving meaningful action. Can you talk about
how you're thinking about that at Humana?
One of the key things with our predictive
models is understanding how to meet members where
they're at and when they are there and
how we make those interactions count. And it's
really around quality over quantity,
how we guide towards the right programs
based on what we know about those members.
And the key to that is how we
use the data that we have. We use,
our predictive models to understand their engagement levels
and their styles.
One of the key examples we have of
that is for example, medication adherence,
medication adherence is one of the key
stars scores as a lot of payers know
that's one of the three weighted stars measures.
And some of the key examples around med
adherence is around social determinations of health, transportation
challenges, financial challenges,
the data that we have around our members
helps us understand what are some of those
key examples of those that what are the
members running into challenges
with and how can we bring information forward.
And when we're talking to those members that
could help them change those outcomes sooner rather
than later.
Those behavior patterns are really critical, and the
predictive models help us understand which members we
need to change up the conversations with. Yeah.
Thank you, Sadie. It and Stuart, what does
what is what Sadie just shared, how does
that sort of align with what you're seeing
among EverRise's other partners, and what what are
your thoughts here?
Yeah. Absolutely. Across the different,
pairs that we're working with,
mainly, they're in different stages, but everybody's working
to to the same set of ideas of
trying to build these big predictive models and
and trying to really
get, proactive and get ahead of the need
instead of waiting for members to call in,
which helps
smooth out the staffing that's needed to things,
but
also makes it more frictionless for the member.
Mhmm. And that that friction that you that
you're speaking to, that claims friction is a
top pain point for for members as well.
Stuart, can you expand on even how you've
seen,
automation or AI materially improve that experience?
What what what have you seen out there?
Absolutely. So so to your point,
when people
are going through a claims process,
typically, they're they're already in a high stress
situation. Right. They're dealing with a health care
issue or maybe an emergency.
So
anything that you put in the way of
them getting to care is just adding to
that frustration, adding to that that that stress.
Something as simple
as through the app,
not just when someone's looking for care, having
it list up a set of providers that
can provide that care, but allowing them through
that app to directly reach out and schedule
that care
just takes a step out of the process
for them, makes it a little bit easier,
makes it a little bit more intuitive,
and and eases that friction for the member.
It's such a good point that they're going
through a challenging experience because people can get
frustrated just when they're calling, you know, their
their bank about an automated thing versus
calling somebody about their own health. The stakes
get higher. People get a little bit more
tense, understandably so. Right?
Yeah. Definitely. I, for me,
grew up outside
US and and and moving here a few
years ago and and and trying to navigate
the health care system, it's not the most
straightforward
process.
Anything that we can do to to remove
some of that confusion, make it it it
more straightforward and ensure that people are getting
the right outcomes and the most cost effective
outcomes
is a huge benefit.
Yep. Yep. Sadie, can you expand on this,
how how you think about,
leveraging AI,
automation to to really improve this experience?
One of the ways that we're looking at
that is also, you know, to Stuart's point,
recognizing
that especially at that claims interaction point is
when the members tend to be at one
of a difficult moments in their life is
how we also smooth it out from the
provider side
and how the providers interacting with the members
using intelligent data automation to reduce the friction
with between payers and providers
from an accounts receivable receivables
perspective is gonna help the providers be there
for the members as well.
In 2023,
there was identified that there was an opportunity
of over $800,000,000
in payments and over a billion dollars in
remit advice.
If providers were able to get to a
full digital adoption for reconciliation.
So there's huge opportunity out there for payers
to work with providers to smooth out those
friction points that that only brings value down
to smooth out those points for the members.
So as we continue
to create those interaction points between the providers
and payers, it's just gonna bring that down
to the members as well. Yeah. And and
can we talk about speaking to sort of,
some of Stewart's points, just the navigating,
some of this stuff is really hard. And
claims education,
is another thing that's really challenging and very
complex,
but very important to do, especially to help
folks understand their benefits, the care they need,
and make sure they're getting the care. Also,
understanding the right side of care. Like, there's
just so much that goes into to education
here. Can you talk about,
Sadie, any any tools you've seen that have
actually simplified,
education member education,
specifically as it
relates to sort of,
open enrollment seems like a a a specifically
challenging moment for folks. So in anything you
can share there. Yeah. That plan education with
members is something that we are continuously looking
at how do we shift that as far
left as possible
in working with members and beneficiaries.
Understanding you know, very similar to where we're
talking about meeting members where they're at,
and using the data that we have with
members, either with their current plans or even
their previous payers,
understanding how they wanna be engaged with and
using predictive models to understand where they're going
to engage more effectively, whether that's with inbound
engagements, outbound engagements, or even digital engagements.
That's gonna help us understand
how do we get in front of potential
health
gaps? How do we help them
understand
what are those
plan opportunities that they may not know about
like transportation benefits that could help them get
ahead of things that whether it's medication adherence,
like we were talking about a minute ago,
whether it's other services that they don't know
that they have an opportunity that they can
tap into sometimes even before their plan effective
date.
So by shifting those conversations further left and
in a way that the member is going
to engage with us in a way that
maybe they didn't know about and ways that
we know that they're gonna step up sooner
because that's how they are more apt to
engage with us is one of our big
focuses. And we get that to that by
using the data in a more proactive manner.
Yeah. Big big component of education here is
letting them know what they've got. Yeah. Because
sometimes they've got they've got coverage for things
that they didn't realize, and I imagine finding
out about that as a positive experience as
well. Stuart, what would you add to this?
In addition to to the area Sadie was
covering, another important part for us, you know,
we we we do build, in our Ever
AI labs. We're working with our clients to
build
technologies,
AI that can directly outreach to the members.
But another important area for us is we've
got a
large contingent
of advocates in our call centers.
And due to the seasonality, you're onboarding people
for the season each year. So building tools
that can help those advocates get to the
right information,
maybe by doing predictive intent modeling and understanding
what a member might be calling about before
they call in or just,
improved
AI back tools to support knowledge bases,
to improve the training process for the advocates
allows them to be more informed
and allows them to provide a much better
level of experience to the member, getting to
the information quicker,
resolving in a single call, something that that
previously might have taken a few calls to
call in. All of these different areas come
together and improve that member experience. Yep. And
what you're laying out here, there's a deep
need for it.
It's very exciting opportunity to be able to
give this to members.
But, of course, we wouldn't be talking about
health care if we weren't talking about hurdles
and potential challenges. So,
we should we should honor those and talk
a bit about those. Stuart, we can start
with you. What compliance or regulatory hurdles are
gonna prove most challenging here, and how can
folks navigate those without losing momentum and and
really still being able to take advantage of
this really excellent opportunity?
One of the areas, funnily enough,
that I've seen as a challenge
is
you've got a bit of a a friction
between
marketing groups at companies such as ours who
wanna plaster AI,
on everything that they're doing in the marketing
material and
technology
groups who rightly
are looking at risk
and have concerns around
how AI is being used.
AI is an umbrella term. It means a
lot of different things to different people, and
it's it's very important to be very precise
in what we're talking about
because,
you may have a solution
that is truly
generative AI interacting
data set that includes member information that really
does need to go through,
full regulatory
body, and and understanding what the implications are
before it gets deployed. But there may be
another technology
that's kind of AI or has very controlled
AI use in a completely ring fenced,
setup that doesn't need to go through that
full full setup. And you can have a
situation where you've got a great tool that
you want to deploy that's gonna deliver fantastic
either cost reductions or improvements or an experience.
And it sits in the back of the
queue waiting to go through that full regulatory
review that probably could go through a faster,
smaller setup. So so for me, that's one
of the areas that's important is
education,
education within our business to understand what we're
really talking about and being a little bit
more precise as we define what these tools
and technologies are and what they do. Yeah.
Cutting through the the umbrella term. Right?
So that people don't just think AI. We
gotta we gotta check this out. This is
gonna take time, and they can they can
then be more, like you said, intentional with
how you're educating about certain solutions.
Sadie, what would you add here?
You know, I think to Stewart's point, one
of our biggest challenges
is actually our internal governance.
And that's part of why, you know, not
only AI, but technologies
moving faster than ever before,
in our lifetime right now. And you need
to have really strong dynamic partnerships
within legal risk compliance and your technology organizations
internally
to keep up with those changes.
And they have to be ready to evolve
and look at from a multifaceted
perspective
what are all of those things that are
changing. And you have to look beyond your
current
industry and understand what else is changing and
start looking ahead.
You have to start looking at what else
is happening across,
the technology
across even across in industries that maybe you
wouldn't anticipate
outside of health care and how that could
be what's coming up in the next six
months, nine months, a year ahead, so that
you can be ready for that to start
influencing the healthcare industry.
And that's how we're gonna start being able
to both understand and partner within governance or
government policy makers to start planning ahead and
making sure we're getting the right outcomes for
our beneficiaries.
I think that's also how we make sure
we're staying focused on the problem at hand
and not necessarily focusing on the shiny object,
which is helps us get ahead of some
of those advertising techniques. Yep. Focusing on the
actual needs,
of your members and not just the the
the technology in of itself. Technology for technology's
sake. Yeah.
It was a real pleasure getting to speak
with both of you today. And before we
sign off, I'll I'll open it up to
each of you to share any closing thoughts
with listeners. Sadie, you can go ahead. Go
first. You know, we were just talking about,
you know, making sure you stay focused on
the problem at hand even if it's not
the sexy one. I think it's staying in
on that same topic.
You need to be, you know, we talk
about, you know, across the industry, folks are
talking about being agile and failing fast, but
you really have to live that and be
willing to pull the plug. If you're not
seeing the outcomes that's expected.
We're seeing that a lot with AI that
you have to be willing to say, if
you're not seeing the outcomes that you were
expecting
and make the changes that you need to
see,
that's really critical to get to the outcomes
that are expected. You know, there's a lot
of big promises out there. If you really
wanna see the outcomes, you have to be
able to make the tweaks and pull those
triggers as you go, and that's really critical
and and be comfortable making those big changes.
Yeah. Yeah. Stuart, what would you add?
It's been a fantastic conference here,
hearing a lot of speakers up on the
stage talking about similar
areas around the technologies.
Obviously, it's a it's an exciting time. It's
a it's a challenging time, but I think
another area that's important with with such a
rapidly
developing set of technologies,
it is easy to get distracted
by by the the marketing spin that's being
put out there and and for everybody to
try and jump on the next shiny object.
So it's easy for companies to to get
kind of a fractured strategy where they're getting
all these promises. There's so many companies reaching
out, and they're they're jumping from solution to
solution and and and kind of over indexing
on on trying a bit of everything.
And and maybe the best approach
is to pick a couple of key partners
that you can work with, that you have
trust with, that you have experience with, that
understand your business needs to your point so
that you can partner on a strategy.
And understanding these technologies, they're evolving so rapidly
that they're gonna leapfrog each other in terms
of the the the immediate deliverables.
So having that slightly longer term view can
get you to better outcomes instead of just
getting drawn in a a thousand directions and
getting nowhere. And you need a partner that's
willing to take that long term view with
you. Yep. And invest with you, I mean,
and and partner. Excellent. Well,
Sadie, Stuart, it's been a pleasure speaking with
you today. I wanna thank you both for
coming on the podcast. I wanna thank EverRise,
of of course, for for sponsoring this episode.
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