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AI ROI: What Early Adopters Are Measuring and Why It Matters · Becker’s Healthcare Podcast

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  Hi, everyone. This is Lucas Voss with Becker's
• 0:02
  Healthcare. Thanks so much for tuning in to
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  the Becker's Healthcare podcast series. Fantastic to have
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  you all. And an exciting topic today, very
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  top of mind for a lot of folks,
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  AIROI.
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  What early adopters are measuring and why
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  it matters.
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  And I'm even more excited to be joined
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  by Alex Lebrun. He's the cofounder and CEO
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  of Nava. Alex, it's so great to have
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  you. Thanks for being here.
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  Hi, Lucas, and thanks very much for having
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  me today. Yeah. Absolutely. I do wanna start
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  off with introductions for those that might not
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  know you yet.
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  Could you just share a little bit about
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  yourself and and your work in health care?
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  Yeah. I'm Alex Lebrun, cofounder and CEO of
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  Nabla.
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  I started Nabla seven years ago.
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  Our our goal has always been to build
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  an AI assistant for for clinician,
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  particularly to to help them to get rid
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  of the the part of their jobs they
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  don't like and whereas they are wasting a
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  lot of time. So the
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  administrative stuff,
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  paperwork.
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  So, yeah, we've been, working on that at
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  Nava for, many years now,
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  reaching today about, 85,000
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  clinicians,
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  millions of, encounters every month. And we have
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  a very ambitious plan to do more and
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  more for our clinicians, as we move forward.
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  I recently had the pleasure to to listen
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  to you at our Becker CEO and CFO
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  roundtable where you're part of a panel.
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  And the discussion really centered around how early
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  AI adopters like UNC Health, Penn Medicine are
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  are defining and measuring ROI right now.
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  When you look back at that conversation,
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  what surprised you most as you were listening
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  to your peers and the conversation itself? And
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  and on the other hand too, what validated
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  what you were seeing and what's happening right
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  now?
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  Yeah. So so what's
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  surprising and amazing is that we really
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  are starting a new phase. Until recently, we
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  were, I think, in phase one of AI
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  deployment in health care
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  where we didn't have hard ROI. It was,
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  like, soft ROI.
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  So making physicians happier, less
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  burnout,
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  less pajama time.
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  People are really happy to use AI.
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  It has an impact. But if you are
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  cynical, you could say, Hey, the CFO didn't
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  see the impact
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  on their
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  numbers.
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  And this was phase one. And I think
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  with more maturity in the field and also
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  with with bigger projects, you know, more investments,
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  now,
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  we are starting phase two where we need
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  to have
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  very, very strong
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  financial ROI when we deploy AI. And it
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  was really,
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  obvious when you listen to the panel, to
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  to my
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  partners of the panel, that they are now
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  we are measuring
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  very, very precise
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  ROI,
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  and it's, it's new, actually. It was not
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  like that just, six months ago.
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  Yeah. We talk so much about the transition
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  from pilot to scalability. Right? Organizations now scaling
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  these initiatives across organizations and obviously measuring ROI
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  around them. And there's so many
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  there's so much of a range for ROI
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  priorities right now. Like, mission alignment,
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  administrative burden is certainly one that's top of
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  mind for a lot of people. Patient trust,
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  a lots of different priorities.
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  From your perspective,
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  what are some of the measures, one, two,
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  or three, that health systems should be prioritizing
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  right now and why?
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  So
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  in my field, you know, in our field,
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  the most impact is the most obvious is
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  the impact the tool has on claims, you
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  know, on on revenues.
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  So and in terms of for new for
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  a new cycle management, you really see
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  how,
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  many clinicians
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  are actually done coding,
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  because they are afraid of audits. They are
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  they're not sure about something, so they tend
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  to miss a lot of
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  of things they should do.
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  And you can really measure the impact of
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  having this AI assistant helping
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  the clinician to code as they are supposed
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  to code, which results
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  in in in, you know, revenues direct directly
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  to revenues, translated to revenues.
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  So this is,
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  and this is why in our in our
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  field, most MBN AI companies are moving fast
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  into,
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  into coding and RCM because this is a
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  very, very strong
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  immediate,
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  easy to measure,
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  kind of ROI.
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  When you think and I agree with the
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  RCM piece. I think that's a lot of
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  conversation that's happening right now. We saw it
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  at the conference too, at the roundtables. A
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  lot of it was RCM focused. When you
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  think about the the partners that were some
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  of your partners that were at,
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  in Chicago there at the roundtable,
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  Can you share some of the examples
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  of health systems that sort of got measurement
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  right of, like, thinking about, okay, this is
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  how we measure ROI, and how did their
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  approach
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  influence also leadership buy in and how these
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  initiatives then scale across organizations?
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  So that's a good question. I cannot speak
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  for them,
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  and I don't remember the the exact,
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  results.
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  And it's it's very new also. I think
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  we should also not exaggerate too much that,
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  okay, we've been doing that for two years
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  and it's we have these numbers.
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  I think I can say, that a few
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  months ago, no no one was measuring this
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  kind of ROI.
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  And we just started to set up the
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  right metrics
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  and KPIs
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  to see, how AI impacts revenues, for instance.
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  So I think the methodologies we've converged
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  to are are good,
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  and we can we should, you know, see
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  you know, meet again in six months and
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  see the actual,
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  what was actually measured. I think it's still
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  early. We should we should be humble.
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  It's still still very,
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  early, but it's definitely
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  the the trend to go there is, I
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  think I think we see at the stake.
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  Yeah. Turning this around, though, to to the
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  leadership piece, because I think, again, change management
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  when we talk about technology and AI is
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  so key because people have to understand that
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  they have to know the benefits that it
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  brings. Right?
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  As we're looking ahead, how would you like
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  to see health care leaders' conversations about AI
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  ROI evolve in in the next couple of
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  years, and what are some of those opportunities
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  that you are excited about?
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  Yes. I think,
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  for an AI tool,
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  if you live in a in a silo,
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  you know, in a in a sandbox disconnected
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  from the rest of the workflows, it's very
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  hard to have a strong ROI. That's why
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  what we do is so difficult.
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  What's exciting now is that
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  as we have more coverage with AI, so
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  there are still point solutions,
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  but we are I think things are in
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  the process to, maybe
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  consolidate, and we'll we'll see more and more,
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  like, end to end solutions built on AI.
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  And once you have an end to end
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  solution going, you know, from
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  the precharting
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  all the way to,
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  reimburse claim and everything is powered by AI,
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  then measuring very strong ROI is is easy
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  because you can follow okay. I did something
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  at the pre pre
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  encounter stage, very, very early stage. But because
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  I see all the process, I can prove
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  that, like, it actually had an impact
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  two months later on revenue connection.
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  You see what I mean? So it's we
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  are excited because this kind of ambition to
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  have an end to end process workflow
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  managed by AI was impossible to even imagine
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  a year ago.
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  And with all the progress we have with,
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  like, agentic approach where
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  we are not afraid to do,
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  to do more automation and to connect different
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  tools together,
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  then we will, quickly,
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  reach this kind of end to end
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  deployments. And for for this,
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  our eye will be so obvious that,
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  you know, metrics will be very, very obvious.
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  So I'm personally quite excited by this,
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  perspective.
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  Well, and what you just mentioned too is
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  so important
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  for scalability,
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  especially as we think about larger organizations,
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  multiple locations, all of that, all of these
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  different components. It's such a key to be
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  able to to to scale these initiatives,
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  for organizations, which is awesome. Alex, it's so
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  great to have you on. I I do
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  wanna leave you
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  with the with the floor for for the
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  final
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  audience?
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  No. Generally, I think people should be aware
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  that it's just the beginning.
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  We should be very excited because this is
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  a beginning, like like, if we were talking
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  Internet in, '97,
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  maybe. So it's not perfect. Many things are
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  still, in progress.
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  And we love, you know, working with partners
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  and customers who really realize that
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  it's not an off the shelf thing that
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  they have to take or not. It's something,
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  you know, we are they have a very
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  strong impact
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  on modeling, on on developing.
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  And I really like to say it's a
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  1%
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  journey done as the journey is done.
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  And we shouldn't the discussion we have shouldn't
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  be, should we use AI or not for
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  this is
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  how should we can we rethink this workflow
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  given the new tools we have and the
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  new powers we have with AI? So this
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  is this mindset, I think we
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  great people have in our, industries.
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  Absolutely. Alex, it's so great to have you.
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  Thanks for your time and insights today. Thank
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  you very much, Lucas.
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  Absolutely. And we also want to thank our
• 9:29
  podcast sponsor, Nabla. You can tune into more
• 9:31
  podcast from Becker's Healthcare by visiting our podcast
• 9:34
  page at beckershospitalreview.com.