Latest / Becker’s Payer Issues Podcast / From Data to Dollars: Strategies to Curb Rising Healthcare Costs

Transcript

From Data to Dollars: Strategies to Curb Rising Healthcare Costs · Becker’s Payer Issues Podcast

• 0:00
  Hi, everyone. This is Lucas Voss with Becker's
• 0:02
  Healthcare. Thanks so much for tuning in to
• 0:04
  the Becker's Healthcare podcast series. Fantastic to have
• 0:07
  you. Today, we're talking about from data to
• 0:10
  dollar strategies to curb rising healthcare costs, a
• 0:13
  very exciting topic, and I'm even more excited
• 0:16
  to be joined by Marcy Tach, executive vice
• 0:18
  president, proven by Meredith. Marcy, it's great to
• 0:21
  have you. Thanks for being here. Thank you
• 0:23
  so much, Lucas. I'm excited for the conversation.
• 0:25
  Absolutely. For those that might not know you
• 0:28
  yet at least, could you start by just
• 0:30
  introducing yourself to our audience and just share
• 0:31
  a little bit about your background in health
• 0:34
  care? Absolutely.
• 0:35
  So my career has been at an intersection
• 0:38
  of technology and health care. So I spent
• 0:41
  many years at McKesson,
• 0:42
  and then changed health care. I joined Meredith
• 0:45
  in 2023
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  running their Curum business, and Curum is in
• 0:49
  the health and human services side. We have,
• 0:52
  lots of international business with that with that
• 0:54
  particular company.
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  Last year, I, moved over to be the
• 0:58
  general manager of Truven.
• 1:00
  And just a a quick overview of what
• 1:02
  Truven does. Truven is a data and analytics
• 1:04
  company that serves
• 1:06
  40% of the Fortune 100 employers, and we
• 1:09
  work with seven of the top 10 health
• 1:12
  plans. We also, Lucas, just,
• 1:14
  acquired Springbok that was in the news last
• 1:17
  month, which added another 7,500
• 1:20
  small to mid market employers into our customer
• 1:23
  base. We're in a really exciting
• 1:26
  place to serve the employers.
• 1:28
  And it's so great to have you on.
• 1:29
  Again, you mentioned all of your experiences, such
• 1:31
  a great perspective, obviously. And then as you've
• 1:33
  just told us,
• 1:35
  so much available information that we're gonna get
• 1:37
  to hear about today, which I'm so excited
• 1:38
  about. And and I feel like this topic
• 1:40
  never really gets old. Right?
• 1:42
  There's a lot of focus on the high
• 1:44
  cost of health care right now specifically. We've
• 1:47
  had those conversations.
• 1:49
  From your perspective, what are some of the
• 1:51
  biggest factors
• 1:52
  driving those costs right now
• 1:55
  and why
• 1:56
  this is really important. Right? Why has it
• 1:58
  been so difficult for organizations
• 2:00
  to really make meaningful
• 2:02
  progress in addressing those costs?
• 2:05
  Great question. So,
• 2:07
  a few examples
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  of what's driving cost would be the aging
• 2:11
  population and chronic disease. Right? So as people,
• 2:14
  get older, the chronic disease is just part
• 2:17
  of that equation.
• 2:18
  That coupled with the complexity
• 2:20
  of our systems
• 2:22
  drive cost up. So
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  most companies, when I when I meet with
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  clients,
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  they want to have
• 2:29
  high quality care for their employees.
• 2:32
  But they're also,
• 2:33
  you know, the the two sides pulling is
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  they're also trying to balance rising costs. So
• 2:38
  benefits for these employers
• 2:40
  is one of their largest expenses. And and
• 2:42
  most people know this, but it's really second
• 2:44
  to cost of goods and services. Right? So
• 2:46
  Yeah. You look at, in 2024,
• 2:48
  this just astounds me, the average annual premium
• 2:52
  per family
• 2:53
  was over $25,000
• 2:56
  for coverage.
• 2:57
  Workers covered 6,000 of that. Employers contributed about
• 3:01
  19,000.
• 3:02
  So the cost is is high.
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  We we know that in 2025,
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  when we end twenty twenty five, we think
• 3:09
  those costs will have risen another 9%.
• 3:12
  So it's just not sustainable. And
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  to your second question of why is this
• 3:17
  so difficult, it's there's a mass amount of
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  data out there. And and because of the
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  complexity
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  of the conditions and the data available and
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  the skywriting cost, companies really need to use
• 3:29
  data and insights that they can drive from
• 3:31
  that data to make better informed decisions. And
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  so when I am talking to companies
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  and health plans
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  and and many of our customers,
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  they're really looking,
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  for data to provide insights
• 3:46
  to make so that they can all make
• 3:47
  much more informed decisions for their population based.
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  And as we know, no two employers is
• 3:52
  the same. You have you have different regions.
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  You have different demographics.
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  And so really diving into that data and
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  making sure your data is curated and accurate
• 4:01
  is really important to really curb that cost
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  for this ongoing trend that we're seeing in
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  The United States.
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  And I think that's even more important now
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  because you've mentioned, you know, aging population, etcetera.
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  There's so many factors
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  driving all of this that you have to
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  have good data to be able to influence
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  and make meaningful change there. And and I
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  think one of the interesting things is, right,
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  we we talk a lot about long term
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  and and short term. Right? Where can we
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  make impact?
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  Where do you see the biggest near term
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  opportunities versus that long term piece,
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  structural fixes right to to really create lasting
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  change in that space? What are some of
• 4:38
  those opportunities that you're looking to right now?
• 4:41
  Sure. So one of the near term opportunities
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  is GLP one drugs. So taking a step
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  back on Truven,
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  one of the the other tools we have
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  in the Truven portfolio is is the MarketScan
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  database, which is a large longitudinal record that
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  we use to help clients do,
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  studies and and help them understand.
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  And what we we know is most clients
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  are seeing skyrocketing
• 5:04
  cost on GLP one drugs. One in eight
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  American adults have taken a GLP one drug.
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  We don't expect this to to to stop.
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  Most of the employers are planning in their
• 5:14
  benefit cycle of how to help,
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  help their employees have access to these drugs,
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  but to do it in a successful way.
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  So these are expensive medications as as most
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  people know.
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  And and to drive an outcome, we're finding
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  in the data shows that the drug plus
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  services
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  actually leads to better results. So
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  we ask employers and when we talk to
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  employers,
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  you they need to combine the drug, the
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  medical,
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  biometric data, lab data, and actually
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  monitor utilization
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  and outcomes.
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  And and when they do that, they can
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  better manage cost. Right? So these drugs have
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  a benefit
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  to many different populations,
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  and so there's a definite need for the
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  drugs. It's just coupling them with the right
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  like, in a weight loss situation,
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  coupling with weight loss services and so that
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  better habits are created for long term so
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  that people maybe don't have to be on
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  the same doses of the GLP ones long
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  term. On a structural side,
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  I I would really lean into,
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  you know, mental health and wellness. So one
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  in five adults who United States adults experience
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  mental health illness.
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  And, you know, we I think we really
• 6:24
  started to see that come to light during
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  during COVID, right, when people were were home
• 6:29
  and more isolated.
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  Employers are offering more mental health resources now,
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  and they they need to help employees engage
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  around those support system. And so there's a
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  lot of point solutions out there.
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  There's a lot of wave ways for companies
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  to combine their data with sociodemographic
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  data,
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  and they can get a complete picture
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  of of the employee and tailor the approach
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  to ensure that that employee is engaged in
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  getting the most benefit,
• 6:57
  for mental health and for their for,
• 7:00
  their illness. And, you know, companies can also
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  use data and some of the research that
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  they can they can get from the data
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  to to hold vendors accountable. There's a number
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  of point solution vendors out there, many very
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  good, but not every
• 7:14
  solution is tailored for every employee population. So,
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  you know, we really like to to tell
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  companies, do you know? Look. You try these,
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  do analysis, see where the return is, and
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  really make sure you're coupling the right tools
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  for your population to get the best the
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  best outcome for those systemic issues.
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  I love that you mentioned the specific approach,
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  right, because I think it comes back to
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  we need a holistic approach that also addresses
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  things like social determinants of health and all
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  of these different aspects, and that's where data
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  can really shine is being able to address
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  some of this. It's it's so, so key
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  and so important.
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  I wanna tie us back to what we
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  originally started our conversation with, which was the
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  high cost of health care. And I wanna
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  talk a little bit about how we can
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  fix this. Right? How we can address some
• 8:00
  of this, how we can make it more
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  affordable.
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  What are some of the strategies and approaches
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  that you've seen actually work when it comes
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  to making health care more affordable? And I'm
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  also wondering if you could share an example,
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  from from your work and from the conversations
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  that you're having that that really illustrates
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  this approach in in action.
• 8:19
  Absolutely.
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  So, again, I I go back to, you
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  know, a data driven approach works best. And
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  I I say that because we all have,
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  you know, our hypothesis
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  when we look at our employee populations of
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  of what is needed.
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  And sometimes we have our own filters, and
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  we don't see the total picture. So, you
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  know, data and a data driven approach,
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  always lends,
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  to the to the to the best
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  ability to follow trends and to look at
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  outcomes and to see, you know, if the
• 8:48
  quality of care is is matching the cost
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  of care. And in many cases, you can
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  drive to quality of care at lower cost
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  of settings potentially. So,
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  one thing Truven has and then I'll
• 8:59
  I'm gonna circle back to your question about
• 9:01
  an example. So Truvent has an interesting portfolio
• 9:04
  of analytic enrichments and models, and we've had
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  this for a number of years. And one
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  of the examples of those enrichments is an
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  episode grouper, and it basically it takes data
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  in, it groups it clinically, and it will
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  look at disease staging. With large data pools,
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  you can actually, with that disease staging, you
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  can learn to manage population risk and drive
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  outcomes. So
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  moving populations from
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  a,
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  like, a stage three of a disease back
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  to a stage two, in some cases, if
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  you think of diabetes
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  or other situations,
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  can drastically reduce the cost. So we had
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  a recent customer
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  who was, you know, looking at moving from,
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  fee for service to value based systems, And
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  they used Truven's medical officer gripper,
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  and they looked at physicians,
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  and they looked at clinical performance and sites
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  of care.
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  And by using that episode gripper, they were
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  able to save 6 and a half million
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  dollars annually.
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  And in overall state, you may say, well,
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  6 and a half is a great number,
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  but not it's, you know, not game changing
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  if your if your total cost is 200,000,000.
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  Right? But if you think there's just little
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  things you can do, if if you started
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  to to cut the cost by a million
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  dollars here and a million dollars there, just
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  by making better choices and and getting,
• 10:19
  patients to the right setting of care at
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  the right time and getting them intervention
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  sooner.
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  These are big steps employers can can take,
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  to manage their population. And with that,
• 10:31
  then they're able to provide additional benefits, right,
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  for for things
• 10:35
  that these employee populations,
• 10:37
  need and want as, you know, as they're
• 10:40
  because benefits, honestly, for these employers becomes a
• 10:42
  differentiation,
• 10:44
  when you're going after,
• 10:46
  employees and you're you're wanting to have
• 10:49
  they want to have the best for for
• 10:50
  their,
• 10:51
  for their teams. And I think, you know,
• 10:53
  really using
• 10:55
  data and these outcomes based
• 10:57
  scenarios allows them more optionality
• 11:00
  for offering more services, which is which is
• 11:02
  really what they wanna do. I think it
• 11:04
  is worth noting one change we're making in
• 11:06
  2026
• 11:07
  is these analytic methods
• 11:09
  and groupers are only gonna be available through
• 11:12
  Truven. And, you know, we we decided to
• 11:14
  do that because we we need to be
• 11:16
  as close to the market as possible. The
• 11:18
  the ability to
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  help with risks in population and drive outcomes
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  is so important
• 11:24
  that getting closer to the clients and understanding
• 11:26
  what their needs are really does help us
• 11:28
  improve our portfolio, which is something our clients
• 11:30
  were looking for. Another approach to making health
• 11:33
  care more affordable. You know, we hear so
• 11:35
  much about AI,
• 11:37
  and and some of the some of the
• 11:39
  challenges, right, with the early stage return on
• 11:42
  investment. But there's things you can do with
• 11:44
  data
• 11:45
  to use it from models and to use
• 11:46
  it to to do predictive models
• 11:50
  that really do help employers
• 11:53
  look ahead
• 11:54
  and and really start to map out the
• 11:56
  what if model. So I think that's really
• 11:57
  important in the future. And, you know, Truven,
• 12:00
  we we
• 12:01
  are always exploring, you know, different ways to
• 12:03
  help, our our customers with you know, to
• 12:07
  to detect the risk of rising costs.
• 12:10
  Let's say I'm a very forward thinking organization.
• 12:13
  I've established all of this. I am looking
• 12:15
  at my data. I'm looking at my analytics.
• 12:17
  But now I I really need to do
• 12:19
  I need to know what to do with
• 12:20
  it. I need to know how to how
• 12:21
  to best utilize this. And I I think
• 12:23
  this is a this is a great question,
• 12:24
  I think, because it it get goes to
• 12:26
  the heart of of some of the issues
• 12:28
  that that we're seeing right now. Right? From
• 12:30
  your perspective and and, again, from the conversations
• 12:32
  that you're having, what should organizations
• 12:35
  prioritize right now to get the most out
• 12:38
  of their data? What's the that key thing
• 12:40
  right? And then, again, tying it back, you
• 12:42
  mentioned the example with the the 6,000,000 savings.
• 12:45
  Right?
• 12:46
  How can insights really help reduce the costs
• 12:49
  and and improve overall value in health care
• 12:52
  when it's done right?
• 12:54
  Yeah. Great question.
• 12:56
  So I would tell organizations they should prioritize
• 12:58
  finding gaps in their pop in their population.
• 13:01
  So there are there's lots of savings to
• 13:04
  be found when you start to look at
• 13:05
  and and really start to break down
• 13:08
  your costs and what's driving those costs. So
• 13:11
  but to find gaps and the right gaps,
• 13:13
  you have to have a holistic view of
• 13:14
  data, which which needs
• 13:17
  data curation and aggregation. So,
• 13:20
  you know, years and years ago, you could
• 13:22
  just have claims data.
• 13:24
  Now, you know, we're in a world where
• 13:25
  there's devices and wearables and all kinds of
• 13:29
  amazing data that you can pull in.
• 13:31
  And, you know, with the right the right
• 13:33
  aggregation can give you new insights.
• 13:36
  I would also say, you know, we're in
• 13:38
  a world where you have to link claims
• 13:40
  data with clinical data, looking at those, you
• 13:42
  know, both what's paid and the outcomes.
• 13:45
  That becomes
• 13:46
  really important to,
• 13:48
  coming up with your
• 13:50
  your strategies of how to impact
• 13:52
  utilization rates
• 13:54
  and and and how to really have the
• 13:55
  best outcomes,
• 13:57
  for these employee groups. And I I I
• 13:59
  gotta be honest. It's hard work.
• 14:02
  As I said, the there's there's more data.
• 14:04
  Like, I I every time I walk in
• 14:05
  the mall, there's there's a wearable. Yeah. And
• 14:07
  I'm thinking to myself, well, what what could
• 14:09
  you do that if you if with that,
• 14:11
  if you aggregated it with all the other
• 14:12
  data I know of that's out there. It
• 14:14
  requires sophistication,
• 14:17
  to bring this all together in a meaningful
• 14:19
  way. And, you know, some some organizations are
• 14:21
  large and they have data science teams,
• 14:24
  and they can do this. You know, others
• 14:26
  need a partner and they need somebody to
• 14:28
  help. And I I just say you have
• 14:29
  to really do, an assessment of where you
• 14:32
  are and what your capabilities are
• 14:34
  because getting that that insight from all that
• 14:37
  data aggregation
• 14:38
  is really valuable in the long term, and
• 14:40
  it's worth the investment.
• 14:42
  You'd asked about an example, so I wanna
• 14:43
  I wanna touch on that really quick. Yeah.
• 14:45
  Yeah. Yeah. Absolutely. Yeah. So we had a
• 14:47
  a large employer we were working with who
• 14:49
  wanted to understand
• 14:51
  why their specialty drug costs were so high.
• 14:53
  And this is a common question. I was
• 14:54
  in a meeting yesterday with,
• 14:57
  a large,
• 14:58
  public plan sponsor, and they had they had
• 15:00
  the same question, like, specialty drugs, specialty drugs.
• 15:03
  So Mhmm. We dug into to their data
• 15:05
  and,
• 15:07
  we found that, you know, there were conditions
• 15:09
  that were driving costs. And when you when
• 15:11
  you took all that and looked at other
• 15:13
  populations,
• 15:14
  we identified
• 15:15
  supplementary treatments like physical therapy
• 15:18
  or alternatives to the highest cost drug
• 15:22
  for conditions like rheumatoid arthritis. And when you
• 15:24
  couple those things together
• 15:27
  while still evaluating
• 15:28
  quality, safety, and effectiveness,
• 15:30
  you can save a significant amount of dollars
• 15:33
  for, for for your organization. So in this
• 15:36
  particular study, they found $50,000,000
• 15:39
  of annual savings just by looking at alternative
• 15:42
  ways,
• 15:43
  to couple
• 15:44
  treatment plans and things that we're working in
• 15:47
  other areas, again, those benchmarks.
• 15:49
  And that's meaningful dollars, right, for an organization
• 15:51
  to take back and then can,
• 15:53
  use for other benefits or other areas of
• 15:56
  care that they're they're needing for their populations.
• 15:59
  And, again, like you said, but you can
• 16:00
  only find those areas if you're actively engaging
• 16:03
  in the data and you have a holistic
• 16:05
  view of it. You have a holistic view
• 16:07
  of what you have available to be able
• 16:09
  to analyze and then then make those decisions.
• 16:12
  Marcy, what a great conversation. Thanks so much
• 16:13
  for being here. I wanna turn the floor
• 16:15
  over to you. Anything else that that you
• 16:17
  wanna mention to our audience that we might
• 16:18
  have not touched on or anything else that
• 16:20
  you think is important for them to know?
• 16:22
  Yeah. And, Lucas, I really appreciate the opportunity
• 16:24
  to talk with you today. You know, before
• 16:25
  I wrap up, I would just say data
• 16:28
  sophistication
• 16:29
  is essential to lowering cost. So we think
• 16:32
  about tools and we think we don't wanna
• 16:34
  spend money on the tool.
• 16:36
  I gave you a couple of examples today
• 16:38
  there. If you just apply the right the
• 16:40
  right data and the right trending information,
• 16:43
  organizations
• 16:44
  can can move the dial on their cost
• 16:46
  while improving the outcome
• 16:48
  for their employees and their beneficiaries, which is
• 16:51
  really what they're looking to do. Everyone's looking
• 16:53
  to have high quality of care.
• 16:56
  Data sources, as we talked about, are there's
• 16:58
  many, many sources in today's world, and
• 17:01
  you can no longer make really effective decisions
• 17:03
  with one or two data sources.
• 17:05
  It's just not enough to meet the challenge.
• 17:07
  So aggregating that data, curating that data,
• 17:10
  ensuring you have the right level of sophistication
• 17:13
  in your organization,
• 17:14
  or or asking for help getting sophistication.
• 17:17
  Organizations like Truven, this is what we do.
• 17:20
  You know, but the cost saving and the
• 17:22
  protection of high quality care is worth every
• 17:25
  effort in this environment. So I encourage people
• 17:27
  just to continue to dig into their data
• 17:29
  and look at all all the possible trends
• 17:32
  and and continue to, you know, look at
• 17:34
  what is best for their employees because no,
• 17:37
  no population is the same, and it it
• 17:39
  does take work. But the as I said,
• 17:41
  the,
• 17:42
  the investment is is worth it in the
• 17:43
  end for these for these employers.
• 17:45
  And don't be afraid to ask for help.
• 17:47
  I think that that's really key as well.
• 17:49
  Really, really important. Marcy, thanks so much again
• 17:52
  for being here and for your time. What
• 17:53
  a fantastic conversation. Thank you so much, Lucas.
• 17:56
  And we also want to thank our podcast
• 17:58
  sponsor, Meredith. You can tune in to more
• 18:00
  podcasts from Becker's Healthcare by visiting our podcast
• 18:03
  page at beckershospitalreview.com.