Hi, everyone. This is Lucas Voss with Becker's
Healthcare. Thanks so much for tuning in to
the Becker's Healthcare podcast series. Fantastic to have
you. Today, we're talking about from data to
dollar strategies to curb rising healthcare costs, a
very exciting topic, and I'm even more excited
to be joined by Marcy Tach, executive vice
president, proven by Meredith. Marcy, it's great to
have you. Thanks for being here. Thank you
so much, Lucas. I'm excited for the conversation.
Absolutely. For those that might not know you
yet at least, could you start by just
introducing yourself to our audience and just share
a little bit about your background in health
care? Absolutely.
So my career has been at an intersection
of technology and health care. So I spent
many years at McKesson,
and then changed health care. I joined Meredith
in 2023
running their Curum business, and Curum is in
the health and human services side. We have,
lots of international business with that with that
particular company.
Last year, I, moved over to be the
general manager of Truven.
And just a a quick overview of what
Truven does. Truven is a data and analytics
company that serves
40% of the Fortune 100 employers, and we
work with seven of the top 10 health
plans. We also, Lucas, just,
acquired Springbok that was in the news last
month, which added another 7,500
small to mid market employers into our customer
base. We're in a really exciting
place to serve the employers.
And it's so great to have you on.
Again, you mentioned all of your experiences, such
a great perspective, obviously. And then as you've
just told us,
so much available information that we're gonna get
to hear about today, which I'm so excited
about. And and I feel like this topic
never really gets old. Right?
There's a lot of focus on the high
cost of health care right now specifically. We've
had those conversations.
From your perspective, what are some of the
biggest factors
driving those costs right now
and why
this is really important. Right? Why has it
been so difficult for organizations
to really make meaningful
progress in addressing those costs?
Great question. So,
a few examples
of what's driving cost would be the aging
population and chronic disease. Right? So as people,
get older, the chronic disease is just part
of that equation.
That coupled with the complexity
of our systems
drive cost up. So
most companies, when I when I meet with
clients,
they want to have
high quality care for their employees.
But they're also,
you know, the the two sides pulling is
they're also trying to balance rising costs. So
benefits for these employers
is one of their largest expenses. And and
most people know this, but it's really second
to cost of goods and services. Right? So
Yeah. You look at, in 2024,
this just astounds me, the average annual premium
per family
was over $25,000
for coverage.
Workers covered 6,000 of that. Employers contributed about
19,000.
So the cost is is high.
We we know that in 2025,
when we end twenty twenty five, we think
those costs will have risen another 9%.
So it's just not sustainable. And
to your second question of why is this
so difficult, it's there's a mass amount of
data out there. And and because of the
complexity
of the conditions and the data available and
the skywriting cost, companies really need to use
data and insights that they can drive from
that data to make better informed decisions. And
so when I am talking to companies
and health plans
and and many of our customers,
they're really looking,
for data to provide insights
to make so that they can all make
much more informed decisions for their population based.
And as we know, no two employers is
the same. You have you have different regions.
You have different demographics.
And so really diving into that data and
making sure your data is curated and accurate
is really important to really curb that cost
for this ongoing trend that we're seeing in
The United States.
And I think that's even more important now
because you've mentioned, you know, aging population, etcetera.
There's so many factors
driving all of this that you have to
have good data to be able to influence
and make meaningful change there. And and I
think one of the interesting things is, right,
we we talk a lot about long term
and and short term. Right? Where can we
make impact?
Where do you see the biggest near term
opportunities versus that long term piece,
structural fixes right to to really create lasting
change in that space? What are some of
those opportunities that you're looking to right now?
Sure. So one of the near term opportunities
is GLP one drugs. So taking a step
back on Truven,
one of the the other tools we have
in the Truven portfolio is is the MarketScan
database, which is a large longitudinal record that
we use to help clients do,
studies and and help them understand.
And what we we know is most clients
are seeing skyrocketing
cost on GLP one drugs. One in eight
American adults have taken a GLP one drug.
We don't expect this to to to stop.
Most of the employers are planning in their
benefit cycle of how to help,
help their employees have access to these drugs,
but to do it in a successful way.
So these are expensive medications as as most
people know.
And and to drive an outcome, we're finding
in the data shows that the drug plus
services
actually leads to better results. So
we ask employers and when we talk to
employers,
you they need to combine the drug, the
medical,
biometric data, lab data, and actually
monitor utilization
and outcomes.
And and when they do that, they can
better manage cost. Right? So these drugs have
a benefit
to many different populations,
and so there's a definite need for the
drugs. It's just coupling them with the right
like, in a weight loss situation,
coupling with weight loss services and so that
better habits are created for long term so
that people maybe don't have to be on
the same doses of the GLP ones long
term. On a structural side,
I I would really lean into,
you know, mental health and wellness. So one
in five adults who United States adults experience
mental health illness.
And, you know, we I think we really
started to see that come to light during
during COVID, right, when people were were home
and more isolated.
Employers are offering more mental health resources now,
and they they need to help employees engage
around those support system. And so there's a
lot of point solutions out there.
There's a lot of wave ways for companies
to combine their data with sociodemographic
data,
and they can get a complete picture
of of the employee and tailor the approach
to ensure that that employee is engaged in
getting the most benefit,
for mental health and for their for,
their illness. And, you know, companies can also
use data and some of the research that
they can they can get from the data
to to hold vendors accountable. There's a number
of point solution vendors out there, many very
good, but not every
solution is tailored for every employee population. So,
you know, we really like to to tell
companies, do you know? Look. You try these,
do analysis, see where the return is, and
really make sure you're coupling the right tools
for your population to get the best the
best outcome for those systemic issues.
I love that you mentioned the specific approach,
right, because I think it comes back to
we need a holistic approach that also addresses
things like social determinants of health and all
of these different aspects, and that's where data
can really shine is being able to address
some of this. It's it's so, so key
and so important.
I wanna tie us back to what we
originally started our conversation with, which was the
high cost of health care. And I wanna
talk a little bit about how we can
fix this. Right? How we can address some
of this, how we can make it more
affordable.
What are some of the strategies and approaches
that you've seen actually work when it comes
to making health care more affordable? And I'm
also wondering if you could share an example,
from from your work and from the conversations
that you're having that that really illustrates
this approach in in action.
Absolutely.
So, again, I I go back to, you
know, a data driven approach works best. And
I I say that because we all have,
you know, our hypothesis
when we look at our employee populations of
of what is needed.
And sometimes we have our own filters, and
we don't see the total picture. So, you
know, data and a data driven approach,
always lends,
to the to the to the best
ability to follow trends and to look at
outcomes and to see, you know, if the
quality of care is is matching the cost
of care. And in many cases, you can
drive to quality of care at lower cost
of settings potentially. So,
one thing Truven has and then I'll
I'm gonna circle back to your question about
an example. So Truvent has an interesting portfolio
of analytic enrichments and models, and we've had
this for a number of years. And one
of the examples of those enrichments is an
episode grouper, and it basically it takes data
in, it groups it clinically, and it will
look at disease staging. With large data pools,
you can actually, with that disease staging, you
can learn to manage population risk and drive
outcomes. So
moving populations from
a,
like, a stage three of a disease back
to a stage two, in some cases, if
you think of diabetes
or other situations,
can drastically reduce the cost. So we had
a recent customer
who was, you know, looking at moving from,
fee for service to value based systems, And
they used Truven's medical officer gripper,
and they looked at physicians,
and they looked at clinical performance and sites
of care.
And by using that episode gripper, they were
able to save 6 and a half million
dollars annually.
And in overall state, you may say, well,
6 and a half is a great number,
but not it's, you know, not game changing
if your if your total cost is 200,000,000.
Right? But if you think there's just little
things you can do, if if you started
to to cut the cost by a million
dollars here and a million dollars there, just
by making better choices and and getting,
patients to the right setting of care at
the right time and getting them intervention
sooner.
These are big steps employers can can take,
to manage their population. And with that,
then they're able to provide additional benefits, right,
for for things
that these employee populations,
need and want as, you know, as they're
because benefits, honestly, for these employers becomes a
differentiation,
when you're going after,
employees and you're you're wanting to have
they want to have the best for for
their,
for their teams. And I think, you know,
really using
data and these outcomes based
scenarios allows them more optionality
for offering more services, which is which is
really what they wanna do. I think it
is worth noting one change we're making in
2026
is these analytic methods
and groupers are only gonna be available through
Truven. And, you know, we we decided to
do that because we we need to be
as close to the market as possible. The
the ability to
help with risks in population and drive outcomes
is so important
that getting closer to the clients and understanding
what their needs are really does help us
improve our portfolio, which is something our clients
were looking for. Another approach to making health
care more affordable. You know, we hear so
much about AI,
and and some of the some of the
challenges, right, with the early stage return on
investment. But there's things you can do with
data
to use it from models and to use
it to to do predictive models
that really do help employers
look ahead
and and really start to map out the
what if model. So I think that's really
important in the future. And, you know, Truven,
we we
are always exploring, you know, different ways to
help, our our customers with you know, to
to detect the risk of rising costs.
Let's say I'm a very forward thinking organization.
I've established all of this. I am looking
at my data. I'm looking at my analytics.
But now I I really need to do
I need to know what to do with
it. I need to know how to how
to best utilize this. And I I think
this is a this is a great question,
I think, because it it get goes to
the heart of of some of the issues
that that we're seeing right now. Right? From
your perspective and and, again, from the conversations
that you're having, what should organizations
prioritize right now to get the most out
of their data? What's the that key thing
right? And then, again, tying it back, you
mentioned the example with the the 6,000,000 savings.
Right?
How can insights really help reduce the costs
and and improve overall value in health care
when it's done right?
Yeah. Great question.
So I would tell organizations they should prioritize
finding gaps in their pop in their population.
So there are there's lots of savings to
be found when you start to look at
and and really start to break down
your costs and what's driving those costs. So
but to find gaps and the right gaps,
you have to have a holistic view of
data, which which needs
data curation and aggregation. So,
you know, years and years ago, you could
just have claims data.
Now, you know, we're in a world where
there's devices and wearables and all kinds of
amazing data that you can pull in.
And, you know, with the right the right
aggregation can give you new insights.
I would also say, you know, we're in
a world where you have to link claims
data with clinical data, looking at those, you
know, both what's paid and the outcomes.
That becomes
really important to,
coming up with your
your strategies of how to impact
utilization rates
and and and how to really have the
best outcomes,
for these employee groups. And I I I
gotta be honest. It's hard work.
As I said, the there's there's more data.
Like, I I every time I walk in
the mall, there's there's a wearable. Yeah. And
I'm thinking to myself, well, what what could
you do that if you if with that,
if you aggregated it with all the other
data I know of that's out there. It
requires sophistication,
to bring this all together in a meaningful
way. And, you know, some some organizations are
large and they have data science teams,
and they can do this. You know, others
need a partner and they need somebody to
help. And I I just say you have
to really do, an assessment of where you
are and what your capabilities are
because getting that that insight from all that
data aggregation
is really valuable in the long term, and
it's worth the investment.
You'd asked about an example, so I wanna
I wanna touch on that really quick. Yeah.
Yeah. Yeah. Absolutely. Yeah. So we had a
a large employer we were working with who
wanted to understand
why their specialty drug costs were so high.
And this is a common question. I was
in a meeting yesterday with,
a large,
public plan sponsor, and they had they had
the same question, like, specialty drugs, specialty drugs.
So Mhmm. We dug into to their data
and,
we found that, you know, there were conditions
that were driving costs. And when you when
you took all that and looked at other
populations,
we identified
supplementary treatments like physical therapy
or alternatives to the highest cost drug
for conditions like rheumatoid arthritis. And when you
couple those things together
while still evaluating
quality, safety, and effectiveness,
you can save a significant amount of dollars
for, for for your organization. So in this
particular study, they found $50,000,000
of annual savings just by looking at alternative
ways,
to couple
treatment plans and things that we're working in
other areas, again, those benchmarks.
And that's meaningful dollars, right, for an organization
to take back and then can,
use for other benefits or other areas of
care that they're they're needing for their populations.
And, again, like you said, but you can
only find those areas if you're actively engaging
in the data and you have a holistic
view of it. You have a holistic view
of what you have available to be able
to analyze and then then make those decisions.
Marcy, what a great conversation. Thanks so much
for being here. I wanna turn the floor
over to you. Anything else that that you
wanna mention to our audience that we might
have not touched on or anything else that
you think is important for them to know?
Yeah. And, Lucas, I really appreciate the opportunity
to talk with you today. You know, before
I wrap up, I would just say data
sophistication
is essential to lowering cost. So we think
about tools and we think we don't wanna
spend money on the tool.
I gave you a couple of examples today
there. If you just apply the right the
right data and the right trending information,
organizations
can can move the dial on their cost
while improving the outcome
for their employees and their beneficiaries, which is
really what they're looking to do. Everyone's looking
to have high quality of care.
Data sources, as we talked about, are there's
many, many sources in today's world, and
you can no longer make really effective decisions
with one or two data sources.
It's just not enough to meet the challenge.
So aggregating that data, curating that data,
ensuring you have the right level of sophistication
in your organization,
or or asking for help getting sophistication.
Organizations like Truven, this is what we do.
You know, but the cost saving and the
protection of high quality care is worth every
effort in this environment. So I encourage people
just to continue to dig into their data
and look at all all the possible trends
and and continue to, you know, look at
what is best for their employees because no,
no population is the same, and it it
does take work. But the as I said,
the,
the investment is is worth it in the
end for these for these employers.
And don't be afraid to ask for help.
I think that that's really key as well.
Really, really important. Marcy, thanks so much again
for being here and for your time. What
a fantastic conversation. Thank you so much, Lucas.
And we also want to thank our podcast
sponsor, Meredith. You can tune in to more
podcasts from Becker's Healthcare by visiting our podcast
page at beckershospitalreview.com.