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From Friction to Collaboration: The Future of Payment Integrity · Becker’s Healthcare Podcast

• 0:00
  Hi, everyone. This is Lukas Voss with Becker's
• 0:02
  Healthcare. Thanks so much for tuning in to
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  the Becker's Healthcare podcast series. It's fantastic to
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  have you.
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  Great topic today,
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  certainly timely. We're talking about the future of
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  payment
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  integrity. And joining me for today's discussion, I'm
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  very excited to have him on, is Brian
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  Berkowitz, chief product officer at Lyric. Brian, thanks
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  so much for being here today. It's great
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  to have you. Absolutely. Thanks for having me
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  on. I wanna start off with introductions for
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  those that might not know you yet at
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  least. If you wanna just tell us a
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  little bit about yourself and your work in
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  health care. Yeah. Absolutely. So I would say
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  I've spent most of my career
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  really focusing on the intersection of technology, health
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  care, operations, and innovation. So I I started
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  early in my career
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  predominantly focused on how I could support health
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  grant health plans in their growth journey.
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  But over time, I really started to see
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  how much growth was hampered by just the
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  high level of misalignment and administrative friction in
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  the health care system.
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  So that experience has really, drawn me a
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  little bit more towards building systems that make
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  health care really work the way it should,
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  which to me is more transparent, more predictable,
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  and and more efficient.
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  Earlier today, I lead our product organization,
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  which means I spend most of my time
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  really thinking about how AI and data can
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  simplify the complexity across the payment ecosystem.
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  Our goal at Lyric is to turn
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  really what used to be more of a
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  adversarial
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  audit and recovery driven part of the industry
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  into one that's powered a little bit more
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  by shared intelligence and trust across the the
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  the payer and plan,
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  dynamic.
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  So for Lyric, our North Star is is
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  pretty pretty simple.
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  I would say accuracy to us builds alignment,
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  and alignment is really what's required to get
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  trust.
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  And when trust exists,
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  simplicity really follows from that, and that is
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  our goal at Lyric is to simplify the
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  the business of care.
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  I'm sure we'll we'll talk about that trust
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  here in a little bit too. I think
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  that's a it's an important conversation to have
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  in the context of our conversation today. You
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  choose a very fitting image, at least in
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  my opinion, to describe today's health care tech
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  landscape.
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  You sort of compared it to a to
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  a battleground with organizations really arms racing to
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  deploy AI driven innovation. There's so much happening.
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  It's so busy.
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  From your perspective
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  today, what's fueling all this competition, and how
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  is it shaping the experience for both organizations
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  and patients?
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  Yeah. Absolutely. I mean, to me, it really
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  does feel like, an arms race. And if
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  we look look back at history, most arms
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  races at their core are fueled by a
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  lack of trust. And I don't think anybody
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  would ever say that the relationship between,
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  a health plan and a provider,
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  the word trust does not come to mind
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  very often. No. So we we we really
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  see this and hear this a lot from
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  our customers.
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  Health plans and providers are both very worried
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  that the other is going to get the
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  upper hand when it comes to the the
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  payment ecosystem
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  and process.
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  So they're both trying to add more and
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  more to their arsenal,
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  to keep up with that.
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  And currently,
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  health plans, providers, startups, everyone is trying to
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  do that in an AI first way.
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  So very exciting,
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  the adoption of AI, but the way it's
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  being done is really starting to fragment the
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  landscape a lot more. So each side is
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  starting to build their own tools. They're using
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  their own data models,
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  and they're really defining their own definition of
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  truth, which instead
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  of building bridges, which we'll talk about, is
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  really starting to build more silos across,
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  you know, what's already a very fragmented
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  system.
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  So what comes of all of that is
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  a lot of duplicated work,
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  added administrative
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  burden, and both kinda go back and forth
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  with their new and and different tools. And
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  then really it's just fueling even more mistrust
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  than was was already there. And all that
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  is distracting from really what the core of
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  health care should be, which is delivering
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  better, more affordable care for patients.
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  But I think we're we really think we're
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  at a turning point where technology
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  has now matured enough
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  that we can actually start creating trust by
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  by design. And And so what I mean
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  by that is if we think about advances
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  in AI, blockchain,
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  and different, privacy preserving
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  computation,
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  it's really making it so we can build
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  a system that can almost create trust in
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  the technology itself
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  versus across the human component of that. And
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  that's gonna be really important when we think
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  about two sides that inherently don't trust each
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  other and how we could build it into
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  a more sustainable framework. So that's really what
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  we're looking forward to is how technology could
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  enforce fairness automatically and
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  systemness that you mentioned,
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  earlier here in in your point that you
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  just made. Because, again, you you've also
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  sort of pioneered a concept called trusted intelligence
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  zones, which is, by its very nature, a
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  concept, a system. Can you walk us a
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  little bit through what that means for you
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  and and why it's important
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  to where we are today?
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  Definitely. Yeah. So to us, a trusted intelligence
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  zone, really by definition, is a secure neutral
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  layer
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  where health plans and providers
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  can collaborate more without giving up control of
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  what's important to them, which is typically
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  their data is a very important part of
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  that. So what it does is it combines
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  AI driven mediation with blockchain accountability
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  and really privacy driven governance
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  to make every decision
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  transparent and verifiable
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  by both sides.
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  So So almost think of it as a
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  a digital trust fabric where instead of both
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  sides sending files and data back and forth
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  and debating whose data is right and then,
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  you know, back and forth more on that,
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  Everyone's getting to see the same validated insights
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  in real time without over having to overshare
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  their proprietary information,
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  which is really gonna be critical to any
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  sort of success, when two sides aren't inherently
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  trusting each other. So, really, what we're trying
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  to get to is where fairness is literally
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  built into the architecture of the technology,
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  and every transaction is traceable.
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  Every model every model is explainable,
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  and everyone is really operating within the same
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  guardrails
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  that they get to be part of the
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  the design when they when they build it.
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  So this is really gonna hopefully turn an
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  arms race in more into more of a
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  collaborative
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  environment.
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  Because right now, you know, trust is really
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  what's stopping,
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  us from really achieving what we could in
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  the in the world of simplification.
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  Yeah. And it also you mentioned silos earlier
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  in the conversation that can help eliminate those
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  silos to be a little bit more effective.
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  And at the end of the day, again,
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  that's a lot of the conversations around AI
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  are being used to how how we strengthen
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  in payment integrity and transparency.
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  Right? And then also, obviously, administrative burden is
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  such a big part of this conversation.
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  How is it helping reduce administrative burden and
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  create more consistent and then also equitable payment
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  outcomes across the industry when we talk about
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  AI?
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  Yeah. We see AI as completely
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  redefining payment integrity. So if you think about
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  traditional
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  payment integrity as it's defined,
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  really what it was was finding a lot
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  of inaccuracies
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  after payment was already processed
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  through very manual retrospective
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  audits that often created a lot of tension
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  between health plans and providers.
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  And now we're shifting towards more of a
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  world where we can detect more before the
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  issue even happens and get it to happen
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  even closer to the point of care, really
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  simplifying the process for everyone that's involved
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  and reducing a lot of the administrative,
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  back and forth that's really been created by
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  the way the process was was defined. So
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  at Lyric, what we're trying to do is
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  is build AI that works hand in hand
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  with the human expertise that is critical,
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  to this industry
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  with our models being able to flag
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  really almost in real time coding inconsistencies,
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  predict certain denials
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  earlier in the process,
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  and then surface anomalies to create more of
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  that transparency
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  and education between,
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  health plans and providers.
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  And what that means is overall, hopefully, fewer
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  audits,
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  fewer appeals,
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  and far less friction,
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  between both sides, ultimately still getting to a
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  very similar outcome. So we think it will
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  bring a lot more
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  consistency,
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  to the way payment integrity is done. So
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  if you think about it, AI can be
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  a lot more consistent than different human, different
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  companies,
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  etcetera, trying to apply similar types of of
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  standards.
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  And then lastly,
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  we just think it will be able to
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  reduce the number of manual touch points. So,
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  yeah, we're freeing people to focus on the
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  most complex issues
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  versus having them
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  repeatedly do kind of the low hanging fruit,
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  which is what the industry has traditionally focused
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  on because of the constraints of of humans.
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  Yeah. Absolutely.
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  One thing that we we touched on again
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  is the trust piece. What we haven't touched
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  on yet is is alignment. Right? I I
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  think we've talked about it a little bit
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  here how important alignment is across,
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  across organizations, across, stakeholders to be able to
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  really operationalize this and scale it certainly.
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  As we're seeing this happen, as health care
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  becomes more data driven, again, accuracy alignment between
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  payers and providers is is very critical, specifically.
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  When you're looking to 2026
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  and and probably also beyond, what are some
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  of the biggest opportunities
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  to build more collaboration
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  and trust
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  across the ecosystem?
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  Yeah. I think 2026
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  is shaping up to me to be a
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  a big year for health care.
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  And why I say that is kind of
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  three big,
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  forces that that I see that will start
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  to converge a bit more. So the first
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  is really around,
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  policy and,
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  you know, what's being called data liquidity.
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  So we are really seeing from a regulatory
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  perspective
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  a really hard push for interoperability
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  and transparency,
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  which means standardizing
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  data,
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  is no longer optional. It's almost gonna become
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  a requirement. And this is by far the
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  most tech forward administration we have seen in
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  a long time, and that's helping drive a
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  lot of that.
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  Second
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  is really
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  what we've already started to see from providers,
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  which is
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  an adoption of AI into everything that's being
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  done. And a lot of that's due
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  to headwinds, financial pressures, etcetera. But
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  providers have taken a a far,
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  quicker path to adopting AI in both clinical
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  usage as well as as rev cycle.
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  And then third, we're starting to see
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  have it's always been there, but another heightened
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  area where both consumers and employers are demanding
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  a lot more clarity in where their money's
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  going and why and how it's being used.
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  And they wanna have answers to that in
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  a lot faster way. So, really, we see
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  that that these trends are gonna push for
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  a lot more required collaboration
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  across the ecosystem
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  to make things work. And so we think
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  this is now the time for really creating
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  that that data collaboration to drive shared intelligence,
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  and that's really gonna be, to me, the
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  most important of of '20,
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  trend of '26.
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  So, you know, when when we can get
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  that data
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  and get that intelligence,
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  then we can start addressing the trust problem,
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  which if we don't get there, we're always
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  gonna be constrained. And so I really think
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  that's gonna be the biggest part of of
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  '26.
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  Certainly a lot to consider for organizations.
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  Brian, it's so great to have you on.
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  So many great insights here. And, again, so
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  many things to think about for organizations. I
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  I wanna turn the floor over to you
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  here as we close out. Anything else that
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  we didn't touch on that that you wanna
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  mention, that might be important for our audience?
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  No. I think just the last point I'd
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  close with is and just reiterating,
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  really, we think trust and safety are the
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  next frontier of innovation. So as people are
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  out there thinking about that, you know, we
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  spent years building automation that is fast, efficient,
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  and scalable,
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  but this next chapter is all gonna be
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  about what's accountable,
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  explainable, and fair. So, you know, when we
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  talk this time next year, the the true
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  leaders aren't gonna be the ones with the
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  flashiest AI tools.
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  They're gonna be the ones who are really
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  designing their ecosystems
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  to have that trust and accountability into what
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  they're doing. And that's that's kind of the
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  the path we're taking at Lyric as well.
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  So I think that's the last piece I'd
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  close with is as people continue to adopt
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  AI, don't forget that trust and safety component
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  is gonna be critical and especially in health
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  care. And I'm
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  certainly looking forward to having this conversation again
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  in 2026
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  to see where we're at.
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  Brian, it's it's so great to have you.
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  Thanks so much for being here and and
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  all of your insights.
• 13:19
  Absolutely. I enjoyed it. And we also want
• 13:21
  to thank our podcast sponsor, Lyric. You can
• 13:23
  tune into more podcasts from Becker's Healthcare by
• 13:26
  visiting our podcast page at beckershospitalreview.com.