Latest / Becker’s Healthcare Podcast / Driving Economic Sustainability in Value-Based Care Through Aligning Data, AI, & Care Delivery

Transcript

Driving Economic Sustainability in Value-Based Care Through Aligning Data, AI, & Care Delivery · Becker’s Healthcare Podcast

• 0:00
  Hello, everyone. This is Erica Spicer Mason with
• 0:02
  Becker's Healthcare. Thank you so much for tuning
• 0:05
  in to the Becker's Healthcare podcast series.
• 0:08
  Today, we're going to talk about driving economic
• 0:10
  sustainability
• 0:11
  in value based care through aligning data, AI,
• 0:14
  and care delivery.
• 0:16
  And joining me for this conversation,
• 0:18
  we have with us Michael Meucci,
• 0:20
  the president and CEO of Arcadia,
• 0:22
  and Sanjay Dadamani,
• 0:24
  founder and CEO of GuideHealth.
• 0:26
  Sanjay, Michael, great to have you on the
• 0:28
  podcast today. Thank you so much for being
• 0:30
  here. Thanks for having us, Erica.
• 0:32
  Well, thrilled to have you both. And before
• 0:34
  we get into our conversation,
• 0:36
  I'd love if you could both share just
• 0:37
  a little bit about yourselves and your work
• 0:39
  in the health care space.
• 0:41
  Michael, if you wouldn't mind kicking us off,
• 0:42
  that would be great.
• 0:44
  I'm happy to. I'm Michael Mucci.
• 0:47
  Arcadia is a business that focuses on partnering
• 0:50
  with health systems, health plans,
• 0:52
  and accountable care organizations to help them
• 0:56
  transform
• 0:57
  the way they deliver care with data to
• 1:01
  activate success in new payment models and ultimately
• 1:04
  move to
• 1:05
  a care model which focuses on
• 1:07
  prevention and proactive care
• 1:10
  and focuses on success in alternative payment models.
• 1:13
  So really topical for the conversation today.
• 1:16
  Absolutely. Thank you so much, Michael.
• 1:18
  And, Sanjay, would love to learn a little
• 1:20
  bit more about you too.
• 1:22
  Yeah. It's great to be on, and especially
• 1:23
  with my good friend and colleague, Michael Mucci.
• 1:27
  We actually first met many years ago when
• 1:29
  they were implementing at UT Southwestern and Texas
• 1:32
  Health Resources
• 1:33
  over their clinically integrated network using Arcadia.
• 1:36
  So it's nice to come full circle now
• 1:38
  and and have this podcast opportunity.
• 1:41
  Guide Health, is the organization,
• 1:44
  that I founded and I'm chief executive officer.
• 1:47
  We are an AI health care platform that
• 1:49
  uses clinical intelligence and human empathy to close
• 1:52
  gaps and make great health care affordable for
• 1:54
  all.
• 1:55
  We're physician led, technology driven, and have been
• 1:59
  working with health systems, clinical networks, and now
• 2:02
  employers,
• 2:03
  to scale value based care, combining AI and
• 2:07
  human centered care management
• 2:08
  into a model that reduces administrative burdens on
• 2:11
  physicians and allows us to lower total cost
• 2:14
  of care at a far different price point
• 2:16
  to scale value based care.
• 2:19
  Sanjay, thank you so much. It's great to
• 2:21
  learn a little bit more about both of
• 2:23
  the perspectives that you're bringing to our conversation
• 2:25
  today.
• 2:26
  And I know we've touched on,
• 2:28
  how your organizations operate in the value based
• 2:30
  care space or just care models that incentivize
• 2:33
  preventative
• 2:34
  care. As we're looking at those care models,
• 2:37
  gain traction in health care,
• 2:39
  there's a lot of conversation about alignment, whether
• 2:42
  that's aligning provider incentives and payment models.
• 2:45
  So I kinda wanna start high level here
• 2:47
  and ask how you're both seeing payment models
• 2:49
  and technology aligning in health care right now.
• 2:53
  I think we're at a a really interesting
• 2:54
  inflection point. I I would say
• 2:57
  the pandemic
• 2:59
  rewinding five years
• 3:01
  proved
• 3:02
  at broad scale that virtual care is a
• 3:04
  viable
• 3:05
  pathway to deliver
• 3:07
  comprehensive care, not for all services, but for
• 3:09
  a lot of services.
• 3:11
  And it also checked the box and helped
• 3:13
  a number of health care consumers
• 3:16
  use virtual care in ways that I don't
• 3:18
  think that they had
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  thought they would before because they had they
• 3:21
  had really no other option.
• 3:23
  And so it was a really defining moment
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  for the the role that technology could play
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  in extending
• 3:29
  the care team, in in many ways, virtualizing
• 3:31
  the care team.
• 3:32
  What happened, though, after the pandemic was a
• 3:34
  lot of the telehealth waivers, a lot of
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  the virtual care waivers expired,
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  and and you started to see a a
• 3:39
  renormalization
• 3:40
  to the way that care had always been
• 3:42
  provided.
• 3:44
  What I'm excited about today,
• 3:46
  and Sanjay and I have spent a lot
• 3:47
  of time talking about this, is
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  a lot of the new payment models that
• 3:51
  are that are coming out of CMMI, whether
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  it's the access model or the lead model,
• 3:56
  really put a focus on
• 3:58
  delivering care through multiple modalities
• 4:02
  and welcoming digital and virtual
• 4:05
  solutions into the care team model
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  as as part of the integrated care team.
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  And and that, I think, is really necessary.
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  You need you need payment models to
• 4:16
  not only promote,
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  but
• 4:19
  permit
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  the role that virtual
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  and technology plays in in care delivery.
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  And and I think what you're seeing more
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  and more, especially as there are continued access
• 4:29
  challenges across the country, you're seeing more consumer
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  demand for virtual care.
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  You're seeing
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  a number of
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  health systems and health plans and and frankly,
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  startups and and large established technology
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  companies come to the table with solutions to
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  address those access challenges.
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  And so you're starting to see
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  a a lot of alignment between the traditional
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  health care stakeholders, the technology companies,
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  the the payers
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  for care
• 4:55
  saying,
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  yes. Virtual has a role. And you see
• 4:58
  consumers demanding it. So I think it's a
• 5:00
  really interesting time where the stars are aligning
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  to really allow us to change the way
• 5:04
  that we think about how to deliver care.
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  To add on to what Michael said, I
• 5:09
  look at this from the lens of one
• 5:11
  wearing a previous hat, having worked at the
• 5:13
  front office in CMMI
• 5:15
  on payment model reform and opt
• 5:17
  payment models. And the second is from the
• 5:19
  view of our customers.
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  We just hosted co hosted,
• 5:24
  a panel of,
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  three great health system leaders
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  at varying stages of value based care maturity
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  that was moderated by Anish Chopra
• 5:33
  who has a a strong lens on the,
• 5:36
  digital health care environment,
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  and this was on economic sustainability.
• 5:41
  And if you look at where these payment
• 5:43
  models have have finally created an opportunity,
• 5:47
  It's on where demand signal
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  has now allowed for better infrastructure
• 5:52
  and more creativity that rewards activities.
• 5:55
  But value based care still requires longitudinal visibility,
• 6:00
  very practical things like attribution
• 6:02
  accuracy and measurement.
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  And so, historically, there was a fundamentally,
• 6:07
  you know, data problem.
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  Now as we've overcome that, we need to
• 6:11
  take these insights and make it an scalable
• 6:14
  action problem.
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  And so it's really about now taking insights
• 6:19
  into execution
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  and integrating opportunities through digital infrastructure and AI
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  so that human trust cannot
• 6:27
  won't be eroded, and we can have still
• 6:30
  continued progress on accountability
• 6:32
  in driving to a greater value.
• 6:35
  I think what's interesting on that point too
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  is
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  we, as consumers of health care, which we
• 6:41
  all are,
• 6:43
  I think are frustrated with the experience. And
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  I don't I don't wanna say that that's
• 6:46
  anyone's fault, but I I was talking to
• 6:49
  Sanjay about this the other day. I had
• 6:50
  a routine
• 6:52
  a routine
• 6:53
  health care event needed a prescription,
• 6:57
  and I wanted to be able to access
• 6:58
  my care team virtually. I just it it
• 7:00
  wasn't available. It wasn't supported by my health
• 7:02
  plan. There wasn't a payment model. And so
• 7:04
  the the alternative is you take two hours
• 7:06
  out of your day, you get in your
• 7:08
  car, you drive to your provider's office, you
• 7:10
  pay to park.
• 7:11
  It it's really disruptive. And so you start
• 7:13
  to think about why people put off
• 7:15
  taking care of themselves, and it's because there's
• 7:17
  a really high burden to do that. Whereas,
• 7:20
  in my case,
• 7:21
  if my plan supported a virtual option,
• 7:24
  if my PCP permit permitted that, like, it
• 7:27
  would have been a much easier experience. And
• 7:28
  so I think you're starting to also see
• 7:30
  consumers start to say, I wanna use services
• 7:33
  like
• 7:34
  One Medical or Teladoc more frequently, and you
• 7:37
  you're starting to even see pharma companies try
• 7:38
  to disintermediate
• 7:40
  that experience by going direct to consumer. So
• 7:42
  I think that there's I think there's a
• 7:44
  lot of opportunity to to redesign the system
• 7:47
  around data,
• 7:48
  around agents, around AI
• 7:50
  that's supporting the care team, not replacing it.
• 7:55
  Such helpful overviews from both of you. And
• 7:57
  as we're seeing
• 7:59
  these evolutions of, you know, more digital infrastructure
• 8:02
  and virtual in infrastructure for care,
• 8:05
  Michael, as you put it, you're seeing kind
• 8:07
  of I think you said the stars are
• 8:08
  aligning in terms of the alignment between payment
• 8:11
  models and technology. So it seems like an
• 8:13
  exciting time with a lot of opportunity,
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  but I'd also love to know how this
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  is all creating
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  perhaps, new risk, and how does risk look
• 8:22
  different today than it did in the past?
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  I'll take that first just because we've been
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  deploying AI at scale in a very big
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  way.
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  And so, historically, risk was retrospective
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  and mainly financial. You were putting in your
• 8:36
  investments, you know, having
• 8:38
  care managers and others and your technology out
• 8:41
  there and measuring performance in the rearview mirror.
• 8:44
  Today, that is not the case. We can
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  prospectively
• 8:47
  predict and use machine learning and data science
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  models
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  in the work we're doing together with Michael
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  on,
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  what will happen, what are we going to
• 8:58
  do about it and right now.
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  And then taking that,
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  not just actuarial risk, but behavioral risk, operational
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  risk, and driving it into,
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  helping to better manage populations.
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  Now we can take on hypertension
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  and uncontrolled hypertension at scale or medication nonadherence
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  and drive to better medication adherence or missed
• 9:20
  follow ups and lost attribution and bring patients
• 9:22
  back into clinics
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  or close gaps and and help with better
• 9:26
  documentation.
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  So the new frontier is really execution risk,
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  and it's, I guess, the developing comfort in
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  around the safety models of integrating AI into
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  real time workflows.
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  I I agree with that. And I think,
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  you know, since
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  we've really been focused on how to integrate
• 9:44
  technology and AI into the care model, a
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  lot of the work we've been doing has
• 9:48
  been based on
• 9:49
  large language models and how good they've gotten
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  at predicting the next
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  token in a sequence, you know, the next
• 9:56
  event that might happen
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  given a pattern that we've trained these models
• 10:00
  on.
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  We're on the on the cusp
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  of seeing the next generation of models, world
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  models, that are that are really focused on
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  you train these by building an internal representation
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  of how the world really works.
• 10:13
  If x happens instead, then y might follow.
• 10:16
  It's it's about
• 10:19
  protecting the next word, the next scenario.
• 10:22
  And I I think that the
• 10:25
  opportunity that sits in front of us is
• 10:27
  really thinking about
• 10:29
  how we plan for the next evolution of
• 10:32
  risk based on the path that technology is
• 10:35
  taking. What I'm really excited about is I
• 10:37
  think that with with the advent of large
• 10:40
  language models and AI agents and world models,
• 10:43
  we can move into a place where
• 10:45
  moving into capitation where we know patients get
• 10:48
  better care,
• 10:49
  more high quality care,
• 10:51
  incentives are aligned, is very reasonable. And it
• 10:54
  and to Sanjay's point, the execution risk is
• 10:57
  starting to be mitigated or minimized.
• 11:01
  Yeah. I appreciate the add on there, Michael.
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  And
• 11:04
  while we're on the topic of AI, I'm
• 11:06
  curious
• 11:07
  as you're seeing
• 11:09
  more models and and infrastructure incorporate AI, large
• 11:12
  language models.
• 11:14
  Do you see AI creating a net increase
• 11:17
  or a net decrease in health care costs
• 11:19
  overall?
• 11:20
  I think right now, AI is very inflationary
• 11:24
  for health care. You know, we're
• 11:26
  applying a lot of AI to
• 11:30
  use cases
• 11:31
  like the revenue cycle or payment integrity, and
• 11:34
  I think that you see a lot of
• 11:37
  really mature
• 11:38
  use cases there. You've, you know, pretty broad
• 11:40
  deployment of AI and ambient listening and coding
• 11:43
  and documentation.
• 11:45
  But I I would say on the long
• 11:47
  term basis, it becomes very deflationary.
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  And
• 11:51
  as we continue to deploy AI, I think
• 11:53
  you're gonna start to see us chip away
• 11:55
  at the the administrative
• 11:56
  burden of health care, the the administrative cost
• 11:58
  burden of health care.
• 12:00
  And I I also do I'm I'm very
• 12:03
  optimistic that it's going to allow consumers to
• 12:05
  become much
• 12:06
  better individual advocates for their own health. And
• 12:10
  we'll see a net long term benefit of
• 12:12
  health status as as individual consumers have access
• 12:15
  to
• 12:16
  smart health coaches that can help them maintain
• 12:18
  their health and overall reduce long term,
• 12:21
  reduce long term costs. But I I think
• 12:22
  in the near term, it becomes very inflationary.
• 12:24
  I'm I'm curious, Sanjay, what you're saying.
• 12:27
  Well,
• 12:28
  a few months ago, earlier in this year,
• 12:31
  in Fortune,
• 12:32
  there was an article by a Wharton professor.
• 12:36
  It was actually entitled Wharton's Great Contrarian Says
• 12:39
  AI Isn't an Easy Excuse to Cut Jobs.
• 12:42
  And the article was about
• 12:45
  how inflationary
• 12:46
  AI was, and they gave a few examples.
• 12:49
  In our own use of AI, we've realized
• 12:52
  that previously unscalable
• 12:55
  tasks, especially in the short term, are now
• 12:58
  far easier to deploy.
• 13:00
  So the example I give is at the
• 13:02
  end of the year, we had two customers,
• 13:04
  one where we needed to make all these
• 13:06
  calls to,
• 13:08
  obtain blood pressures
• 13:10
  from the patient and report them.
• 13:13
  And,
• 13:14
  you know, similar such task with another customer,
• 13:17
  similar numbers, ironically, about a thousand outbound calls.
• 13:20
  It took us four hours with AI,
• 13:23
  and,
• 13:25
  I think,
• 13:27
  we were able to complete, you know, get
• 13:29
  to the goals of, you know,
• 13:31
  successfully documenting several 100 of these,
• 13:34
  calls end to end.
• 13:36
  We actually, for the other customer, used our
• 13:38
  our call center.
• 13:40
  And we paid time and a half after
• 13:42
  5PM, and we got the work done by,
• 13:44
  like, 09:00 at night. We pulled 22 people
• 13:47
  off the grid to do all this extra
• 13:49
  work.
• 13:50
  And you can only imagine the staggering costs.
• 13:53
  So I think there's already evidence
• 13:56
  of scalability.
• 13:57
  The question is long term sustainability
• 14:00
  to ensure that
• 14:01
  the overall costs
• 14:03
  are, you know, managed and that it ultimately
• 14:06
  becomes deflationary.
• 14:08
  Sanjay, thank you. And what you're hitting on
• 14:11
  here and Michael as well is something that
• 14:12
  we hear across leadership conversations when it comes
• 14:15
  to AI.
• 14:16
  Leaders are under a lot of pressure from
• 14:18
  their boards and their peers to prove long
• 14:21
  term value, not that a quick pilot AI
• 14:24
  project is working, but in the long term,
• 14:26
  what's the value it's generating?
• 14:28
  So that that leads me to my next
• 14:30
  question.
• 14:31
  I know you've both shared a couple of
• 14:32
  examples of how AI is generating efficiency, augmenting
• 14:35
  teams, but is there a specific example that
• 14:37
  stands out to you where AI is decreasing
• 14:40
  costs right now?
• 14:41
  Yeah. I
• 14:42
  mean, I'll touch on it, and then I'll
• 14:44
  turn to Michael.
• 14:46
  But we had a great example where
• 14:49
  and Michael spoke to this.
• 14:51
  Engaging consumers
• 14:53
  is a really great opportunity
• 14:54
  in value based care.
• 14:56
  And
• 14:57
  no better example than making a series of
• 15:00
  calls to patients
• 15:02
  using AI to get them comfortable
• 15:04
  with the chronic medications that they were taking
• 15:08
  for their underlying chronic conditions
• 15:10
  and converting those to ninety day prescriptions as
• 15:13
  part of a MedAdherence,
• 15:15
  quality exercise
• 15:16
  actually led to
• 15:18
  many more patients
• 15:20
  understanding their medications,
• 15:22
  wanting their pharmacists involved,
• 15:24
  and where their pharmacist pended those prescriptions to
• 15:27
  ninety days.
• 15:28
  We had, you know, fewer gaps in therapy,
• 15:32
  as well as,
• 15:33
  some really beneficial impact on getting patients to
• 15:36
  take their medications.
• 15:38
  And so there are far greater opportunities, I
• 15:41
  think,
• 15:42
  using AI to engage patients, and patients are
• 15:45
  very ready to do that. So
• 15:47
  there there's a huge growth of use cases
• 15:50
  and different applications.
• 15:51
  I just say that we're at a point
• 15:53
  now where we can translate directly into improved
• 15:56
  quality scores, millions of dollars in value based
• 15:58
  performance, and actually better engaged patient care.
• 16:02
  I agree with that. I think one of
• 16:04
  the the most exciting examples
• 16:06
  that I've seen is is solving for
• 16:10
  some of the highest cost parts of health
• 16:12
  care. When you when you think about where
• 16:14
  we we rack up a lot of cost
• 16:16
  in health care, it's oftentimes
• 16:18
  around
• 16:19
  transitions
• 16:20
  and
• 16:21
  either entering into a into an inpatient facility
• 16:24
  for a procedure or an acute event or
• 16:25
  exiting from that. And
• 16:28
  we've been able to orchestrate systems where
• 16:31
  when we see those transitions happening in real
• 16:34
  time, deploying a set of agents to
• 16:36
  message and communicate with patients and members of
• 16:39
  their care team,
• 16:41
  creating visibility around the event, because oftentimes, it's
• 16:44
  the visibility that's lost. You know, to Sanjay's
• 16:46
  point, a lot of health care is done
• 16:47
  driving in the rearview mirror.
• 16:49
  And in addition to that, deploying an agent
• 16:51
  to engage the patient to help them understand
• 16:54
  what role they have in helping navigate the
• 16:56
  transition
• 16:57
  and offering them resources, whether they're
• 17:01
  AI driven resources or escalated to a human,
• 17:04
  to help them navigate that transition, you know,
• 17:06
  out of a hospital into a rehab or
• 17:08
  from a rehab to home or from a
• 17:10
  hospital to home with with home therapy.
• 17:12
  Those programs have been
• 17:14
  both really supportive of helping patients at times
• 17:17
  where
• 17:18
  they often don't know what the next step
• 17:20
  is, and they're overwhelmed, and they're they're they're
• 17:23
  transitioning,
• 17:24
  but also
• 17:25
  helping to manage
• 17:27
  next twelve month cost. And we've seen dramatic
• 17:30
  reduction of next twelve month cost for those
• 17:32
  patients who engage with those resources because they're
• 17:35
  able to be
• 17:36
  better
• 17:38
  activated in helping manage their health, and their
• 17:40
  team is better activated as well.
• 17:43
  Yeah. I appreciate you both sharing those examples.
• 17:45
  So sounds like improved quality scores and
• 17:48
  the significant amount of money that can come
• 17:50
  from that as well as supporting patients through
• 17:52
  care transitions are are two great use cases
• 17:55
  that you're both seeing.
• 17:56
  And as we close our time together, I
• 17:58
  wanted to zoom back out again and just
• 18:00
  kind of reflect on
• 18:01
  the fact that health care is the country's
• 18:03
  largest industry and employer. And so I'd love
• 18:06
  to know from you both how you think
• 18:08
  AI
• 18:10
  will transform,
• 18:11
  and really impact the financial sustainability
• 18:14
  of health care, especially in rural communities.
• 18:17
  Well,
• 18:18
  we've certainly come to that inflection point that
• 18:21
  Michael described.
• 18:23
  Operating margins are exceedingly low. There's health care
• 18:26
  inflation that has been, you know, uncontrolled,
• 18:30
  and we've, you know, risen in degrees of
• 18:32
  complexity.
• 18:34
  And so there has to be something
• 18:36
  that's powerful enough to unlock these increased operating
• 18:40
  margins,
• 18:41
  reduce the administrative burdens, and allow us to
• 18:45
  scale up. And so that's where we're betting
• 18:48
  on AI.
• 18:49
  And I think nowhere more than we know
• 18:52
  that this can support,
• 18:54
  scaling for work that's vital in rural as
• 18:58
  well as underserved communities,
• 19:00
  even in our urban areas.
• 19:02
  We don't have the luxury of time or
• 19:04
  the luxury of adding more clinicians.
• 19:07
  We really have to ensure that AI becomes
• 19:09
  a force multiplier.
• 19:11
  That's why we've taken the approach of integrating
• 19:13
  this into our own,
• 19:16
  services to help, scale up our services to
• 19:19
  have really good data and then to be
• 19:21
  able to drive those insights into actions
• 19:24
  to extend the capacity,
• 19:26
  maintain access, and improve access overall, and then
• 19:29
  shift the resources towards high touch as Michael
• 19:32
  described
• 19:33
  so that those high needs patients can really
• 19:34
  get timely resources for their management. So I'm
• 19:38
  a big fan of this move in this
• 19:40
  direction, and I think
• 19:41
  the
• 19:42
  patient populations that are most in need, those
• 19:45
  medically underserved as well as in rural areas,
• 19:48
  will be the greatest beneficiaries of our time.
• 19:51
  I think you said that exceptionally well.
• 19:53
  You know, when we think about health care
• 19:55
  being one of the largest employers of our
• 19:57
  economy,
• 19:58
  we do not see a reduction of demand
• 20:01
  coming for health care services.
• 20:03
  We also can't ignore the fact that today,
• 20:06
  we don't have enough capacity
• 20:08
  in
• 20:09
  care teams or really even in the administrative
• 20:11
  side to to meet that demand today. We
• 20:14
  have patients
• 20:15
  across the country who are waiting
• 20:17
  far too long to receive care. So as
• 20:19
  we as we think about AI transformation,
• 20:22
  I really think about this as a shift
• 20:23
  to the left. We're gonna allow
• 20:25
  every member of the health care workforce to
• 20:27
  work
• 20:28
  at a higher license.
• 20:29
  People may not have the same job tomorrow
• 20:32
  that they have today,
• 20:34
  but I am almost certain that there will
• 20:36
  continue to be
• 20:37
  a large and robust and very viable health
• 20:40
  care workforce across the country.
• 20:42
  The worst thing for rural communities is the
• 20:43
  closure of a hospital. I think that AI
• 20:45
  and technology transformation
• 20:47
  can save a lot of these facilities, especially
• 20:49
  as you're able to participate in new payment
• 20:51
  models.
• 20:52
  And that that supports the vitality of these
• 20:55
  rural communities that need to be that need
• 20:57
  to be propped up. And I I think
• 20:59
  that we owe it to ourselves and to
• 21:02
  all health care consumers to really think about
• 21:04
  how to how to drive
• 21:06
  that experience
• 21:07
  and support these communities.
• 21:10
  It's an important sentiment to end our conversation
• 21:12
  on. Michael,
• 21:14
  Sanjay, I just wanna thank you both again
• 21:16
  so much for your time and your insights
• 21:18
  today. A lot of great thought leadership throughout
• 21:20
  this discussion. So, just wanna thank you again
• 21:22
  for making the time. Thank you. It was
• 21:24
  great talking today. And we'd also like to
• 21:26
  thank our podcast sponsors for today, Arcadia and
• 21:29
  Guide Health.
• 21:31
  Listeners, be sure to tune into more podcasts
• 21:33
  from Becker's by visiting our podcast page at
• 21:35
  beckershospitalreview.com.