Everyone. This is Lucas Voss with Becker's Healthcare.
Thanks so much for tuning in to the
Becker's Healthcare podcast series. It's fantastic
to have you excited for today's episode
from reactive to proactive
AI's role in the next generation of care
management. And joining me for today's discussion, very
excited to have them both on, Michelle Fullerton,
vice president care management and customer consulting at
Blue Cross Blue Shield of Michigan, and Connie
Duquesne, senior vice president strategic solutions of MindYou.
Michelle and Connie, thanks so much for being
here today. It's great to have you.
Excited. Happy to be here. Absolutely. It's great
to have you. We'll start off with introductions,
for our audience here. Michelle, why don't you
kick us off? Can you share a little
bit about your background and your work in
health care?
Sure. Well, hi, everyone. I'm Michelle Fullerton. I
am a nurse. I'm also a certified case
manager. I have been with Blue Cross Blue
Shield of Michigan
for twenty eight years,
have worked in a variety of roles as
a nurse on the phone with patients,
all the way to now being the vice
president of care management, but I've also worked
with our group customers in population health.
I love care management. I think it's a
wonderful profession,
and I think that we are the core
of what a health plan can deliver to
help patients
when they're in their times of trouble.
Absolutely. Connie, over to you.
Yeah. So thank you. So first, I wanna
say I agree with Michelle
core of care with land with the care
managers.
My background is telephonic intervention,
call centers. I'm a behavior change professional.
So I have more decades than I should
probably say on this,
podcast
experience.
But now I have the opportunity to bring
those skills to MindYou
to help
payers and providers and other groups sort of
think about how do we incorporate what we
do here at MindYou into their current processes
and sort of reimagine
how could they use
AI,
mind you, Eleanor,
in providing care to their members and patients.
Absolutely. And it's a very interesting topic because
it's developing so much for so many organizations,
and it's constantly developing. It seems like every
single day, there's something new. Right? New news,
new technology. And this was an interesting stat
from from McKinsey.
In 2024,
70% of US health care organizations were exploring
or already using AI across clinical and administrative
functions. So, really,
most of the industry were already there, and
we know it's a critical part of care
management.
Michelle, I'd love to start with you on
this.
How are you using AI today,
and what's really motivating
continued investment in these technologies for you and
your teams?
Well, for every leader of care management,
this is all about our cost to deliver
and how to be more efficient
and also letting nurses
perform
all of their tasks at the top of
their licensure. I think those are three
huge factors
that drive
what care management is all about. We have
a large organization
between commercial and Medicare Medicare Advantage Care Management.
We have over 500 employees.
Mhmm. That is expensive.
Nurses are expensive. They're an extremely
important asset,
but we need to use them efficiently,
effectively,
and
also
at top of license.
So those are really three drivers that have
always driven us in how we create our
care management programs.
Yeah.
So
AI
has stepped in
to help us become more cost efficient.
Which is a a key driver, obviously, as
you've mentioned for a lot of organizations. And,
again, we have that 70% number.
Connie, I'd love to hear your perspectives on
this too,
specifically around that second part, which I think
is very interesting, right? Why now? Why is
this happening now? Why are we seeing this
great increase, the 70% number? Why are we
so many organizations going that route?
Well, there's always been a need to do
more with less.
Right? And that's even magnified,
I think,
more now than ever.
And
more and more people are getting comfortable
with the utilization of AI. Right? So so
organizations
are getting comfortable whether you they're using it
for stratification
or ambient listening, whatever the reason
that organizations are getting comfortable and humans are
getting comfortable. Right? So we are using a
AI more and more. I mean, it's 01:00
in the afternoon, and I've already used AI
a half a dozen times,
and I'm not alone. I think if we
all step back and looked at our lives,
we would say, everybody's using it. So let's
find more ways to bring the tools to
the workforce
so they can, you know, create more space
in their day to do the important work.
Yeah. Just as a follow-up to that, Connie,
really quickly, are are you feeling like leaders
are understanding that more and they're bringing in
more of that expertise to be able to
say, this is how we can use AI
better?
I think so. I I think there's a
a lot of information, podcasts like this, a
lot of written materials
that are helping people to to know more,
appreciate it more, and so they're leaning in.
So it isn't just me going out to
payers and saying, hey. You should check out
this technology.
There are payers coming to us saying, we
wanna check out your technology.
Yeah. Yeah. How can we be more efficient,
which Michelle mentioned, right, efficiency across a large
employee base. And, again, I I think the
the top of the licensure is such a
big and important piece of the puzzle for
a lot of organizations.
Michelle, I'd love to come back to that
too in terms of the use cases that
you have,
for your organization specifically.
Can you expand a little bit on on
some of the use cases and especially what
outcomes you've seen? How have they
affected your your teams and especially the workflows,
etcetera? What are some of the things that
you're seeing there?
Absolutely. I would love to talk about this
because I will tell you I was probably
one of the doubting Thomases at the very
beginning of AI,
and I would say that AI,
does not replace a nurse.
Yeah. But what I have learned is that
AI can aid a nurse, and it can
aid in our workflow. So number one, we
use a lot of AI in our ID
and stratification
of patients.
Mhmm. Then of any care management program for
anyone that's listening, we all do the same
thing. We have to reach out to members,
and we have to try to engage them
in our programs, whatever those programs may be.
It may be a rising risk. It may
be an ER reduction.
It may be a disease management program,
but we need to reach out to members
and engage them in our program with our
nurse. Yeah. Well, I call that dialing for
dollars. If you have a 100 nurses
that are on a phone
calling patients
and you only get a hold of 50
of them and then you only gauge, you
know, another 30,
there is a lot of
work left on the floor, right, on on
the Cutting Room Floor. So
why do we not use AI
more effectively and efficiently
in these work processes?
And that's what made me
my ear started to listen
when Connie was presenting
what they do in an organization
and how their use case could help me.
Yeah. Absolutely.
Connie, this is a the the dialing for
dollars piece is a is a great transition
for me
because I think that's where it gets sort
of the rubber meets the road to bring
in another cliche. Right? Is how do we
evaluate this? I'm spending money, but I wanna
make sure this actually works.
When in your conversations with leaders,
when it comes to evaluating ROI,
what are some of the metrics or outcomes
that you're specifically looking for
that leaders should prioritize?
Yeah. So
it's a good question. So
it often starts with a conversation about ROI,
but then when we keep talking, it's really
about value. What value are you gonna bring?
And so there's three categories. There's the efficiency
component,
there's a quality component, and then there's an
economics component.
So depending on the program will determine
what does value look like. So, for example,
Michelle referenced some of these already. Let's say
it's about
supporting a person who was
recently discharged from the emergency department.
We can measure the value
of
the patient
selecting the right type of care,
potentially PCP or urgent care
as compared to an ED. We can quantify
that.
Others are harder to quantify.
For example, if we call 50,000
patients whose provider went out of network
and we want to help them get connected
with a new provider,
that's harder to quantify. It's important, but it's
not as easy to measure. And then there
are those that are sort of in the
middle. And this one, Michelle has referenced a
couple of times. It's helping
the
care managers, the nurses
work top of license
by taking
low skilled tasks
off their workload. That's measurable.
But what's not measurable is what does that
do to the quality of their work life?
Right? How do we measure that? So some
are very concrete and some are softer, but
there are a lot of different ways of
measuring value.
And those that I'm talking to are looking
at all three of those buckets,
efficiencies,
quality, and economics.
Yeah. And those are the primary ones that
that organizations should be looking at, leaders should
be looking at.
When we measure this this ROI piece, taking
a step back here really quickly,
can you touch on some of the use
cases that you've seen where this IUI is
ROI is, like, clearly showing, okay, this makes
the most sense,
how it's affecting teams, etcetera. You've mentioned the
the work life balance piece, right, that's hard
to measure, etcetera. Can you touch on those
use cases, and and which ones are important
to you, and which ones are are have
you seen make the biggest difference?
I certainly can start, and I'll let Connie
finish. But,
let's just take
avoidable
ER visits or
talking to every patient who's been in the
emergency room.
So we can identify people that we wanna
reach out to who we feel
maybe they shouldn't have been in the ER.
They're paying a high co pay when they
go to an ER when they could have
done telehealth or they could have gone to
an urgent care. And number two is when
they get home, are they okay?
Did did their issue
get resolved, or do they need to follow-up
with their primary care physician? If they don't
have a primary care physician, how do we
get them one? So there are many scenarios
just with ER. Now in our program today,
I may only be able to reach out
with the capacity that I have with my
nursing staff. I may only be able to
reach out to, let's say, 200 members a
day. But in our book of business,
maybe we had 500 members that went to
the ER
yesterday.
We wanna reach out to all 500.
We can do that
with
Eleanor. Right? Eleanor can make those calls.
So then
Eleanor can make those calls, and if the
member wants to talk to a human,
we let them come through to talk to
a nurse.
But many times, surprisingly,
the patient is just happy to talk to
Eleanor,
and Eleanor can call the patient back. They
monitor the patient. How are you doing today?
Can I call you back next week?
So all of that work, all of that
phone work has now been taken over by
Eleanor,
but, also,
it allows the nurses to get the cases
that a member wants to talk to a
nurse. Right? But, also, that patient has now
been reached we've reached 500 of them versus
200.
That's powerful.
Right? And what you've mentioned, it's that tandem
work of provider and AI working together. Right?
It's not the the we're not eliminating one
or the other.
It's that that working together that really makes
a difference. Connie, feel free to weigh in
here too and on on your thoughts.
Yeah. So always, it's about augmenting
the clinical staff. Right? So we're the clinical
staff's plus one.
But there's a lot of work we can
do
where the majority of it, 85, 90% does
not require a human. So, potentially, it's making
outreach calls for vaccinations in the fall and
to help people see the value of getting
vaccinated. It's calling patients that are newly diagnosed
with diabetes
and educating them and then tracking with them
and only sending them to a nurse when
there's a need for a nurse. Right?
And so,
Michelle made a comment that people are happy
to talk to Eleanor, and that is a
true statement. We have people who have talked
with her
for months. Right? And then we have some
outliers that we will say have maybe done
it for years. Right? So people
feel safe and cared for
when an empathetic
voice
is outreaching. So I I you know, just
to be very specific about this is Eleanor
calls patients directly,
and she's talking to them about what's going
on in their world and then transferring when
needed. So there's a whole host of use
cases where
the patient wins,
the provider wins, everybody wins because the patient
member feels heard.
We're not losing the human touch even though
we have an AI piece in Eleanor that
takes care of an automated task piece, which
is important. We're we're feeding volume, which is
very important.
And then your
use cases become limitless.
How do you integrate this into your program?
So to anyone else that's running a program,
you know,
ER is just one use case, but there
are so many different use cases.
And that is the fun part of AI
is
just the creativity
of how you integrate this. But you do
so for all of those listening, you do
need to integrate it into your
processes. That's the work. Integrating it into your
workflows,
training your staff all about AI. Those are
two very important things.
But then
the potential is seen by everybody. And so
we have our nurses
creating new workflows and asking, why don't we
use AI for this? Yeah. So it is
exciting.
Once you get your hands in there and
start to use it, you can see a
lot of different potential
use cases
for other things that you do.
Yeah. And and we've touched on this earlier,
in the conversation as well. Right? This is
a a complex space. There's a lot happening.
It can be intimidating. There's a lot of
questions. A lot of folks don't necessarily know
how everything works.
Michelle, I'd love to stay with you on
this. You've touched on it just a little
bit here in your answer.
But what's the the one piece of advice
that you have that you want to offer
peers that are looking to integrate more AI
into care management programs?
Where should they start,
and what should they try to avoid?
Sure.
AI is not gonna solve the entire world,
which some people promise. That is not true.
AI is not going to replace
nurses' jobs.
Those are two big things.
Then number three is don't be intimidated
by AI.
Every leader in care management
knows that we must constantly change.
Adaptation and change
is in our DNA as a case manager,
and this is just
a new technology
that helps nurses
work at top of licensure.
And don't be afraid
to test it. So go small. Test one
small thing
and become comfortable with it. Let your teams
become comfortable with it. And
then you know
that as people become more comfortable, they will
see the potential,
and the use cases will grow. So start
small. Don't be intimidated
and start small.
Dave mentioned the workflow integration piece, which is
so important to let teams explore how it's
working within their own workflows
so they feel like they're still in charge.
Right? It's not taking Absolutely. What they're doing,
which is so important. Connie, same question for
you. What are the some of the things
that you're talking about in terms of, hey.
This is what folks should pay attention to.
This is what they should they avoid.
What are your thoughts?
Yeah. So so one of the things that
we encourage people to do is ask
solution partners hard questions.
Ask about how are you training the models
that you are using.
How do you prevent
hallucinations?
How are you going to attend to a
critical issue? If
technology if in our case, Eleanor is talking
to a person
and a person is expressing
suicidal ideation,
what are you gonna do? So ask the
hard question.
Right? And,
solutions that have been in practice
for a while will have protocols for those
things,
and you will get the answers. One of
the things that we've created is a list
of questions that the people we're working with,
payers, providers, whoever, here's a list of questions
that you will wanna consider asking anyone who
is going to be speaking with your patients
and members.
Yeah.
Right? So you can feel confident to Michelle's
point that
the solution isn't overpromising,
but that they are gonna deliver
or overdeliver.
Right? So good questions make a big difference.
Can I possibly end with a wonderful case?
I find giving people real life cases
helps people understand how this works. Sure. So
we're calling patients who have been to the
emergency room, checking in on them, making sure
they're okay.
First of all, for all of those that
are listening, we have a 72%
answer rate. So 72% of the people we're
calling are answering the phone and talking to
Eleanor.
In this situation,
Eleanor talked to a patient
who asked to be transferred
to a nurse case manager
because she was having palpitations,
and she couldn't get an appointment with her
cardiologist
within the next week.
And she was nervous. She didn't know what
to do. This is exactly the patient that
will go back to the ER, right, because
she can't get in to see the cardiologist.
Call was transferred from Eleanor
into our care advocate program.
Advocate
picked up the call, talked to the patient,
turned around,
called the doctor's office,
and got the person in the next day
with their specialist.
That is advocating for the member,
and
we avoided a future ER visit.
That's where she would have gone.
So isn't that a wonderful story?
Yeah. Absolutely. Again, it it illustrates partnership. It
illustrates
understanding it, what it can actually do. So
I appreciate you sharing that because, again, I
agree. Use cases are very important for folks
to understand how this actually works.
Michelle and Connie, thank you so much for
taking the time today. This was a fantastic
conversation. So many great insights. Thanks so much
for being here.
Appreciate the help of you today. Yes. Absolutely.
And we also want to thank our podcast
sponsor. Mind you, you can tune in to
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