Latest / Becker’s Healthcare Podcast / Garrick Stoldt, VP Finance and Chief Financial Officer at Saint Peter's Healthcare System

Transcript

Garrick Stoldt, VP Finance and Chief Financial Officer at Saint Peter's Healthcare System · Becker’s Healthcare Podcast

• 0:02
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  Hello, and welcome to the Becker's Healthcare podcast.
• 0:35
  My name is Will Riley from r one.
• 0:38
  I am joined today by Garrick Stolt. Garrick
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  is the chief financial officer at Saint Peter's
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  Healthcare System in New Jersey. Garrick, welcome to
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  the podcast.
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  Well, thank you very much for having me.
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  Thank you.
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  To start off, can you tell us a
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  little bit about you, your role, and St.
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  Peter's?
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  So St. Peter's is in Central New Jersey.
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  We are a single hospital system.
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  Actually, I was looked at my email this
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  morning, and Becker's came out with the 51
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  best surgical outcome hospitals in the country, and
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  we were on that list. Congratulations. So I
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  thought it was kind of interesting to start
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  the day off with that.
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  But we're a single hospital system, 478
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  beds, major teaching. We have a lot of
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  specialty service. We're known for women and children
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  services in particular. We're also a safety net
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  hospital, so we have a high percentage, about
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  25% Medicaid. So that makes a little more
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  challenges, especially in light of the big beautiful
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  bill that just got passed. Sure. Tell us
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  a bit more perhaps about the community around
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  you, the community that you serve. So New
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  Brunswick,
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  is there's 580
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  municipalities in New Jersey, and New Brunswick has
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  the fourth highest percent of the population living
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  below the poverty guideline. And you wouldn't know
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  it because it's really a revitalized city. But
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  right in the middle of Rutgers, it's the
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  home of Rutgers, it's the home of J
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  and J, There's another large health system, which
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  I won't name. That's right in our backyard
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  or just about a mile from us. So
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  highly competitive market.
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  There's a number of hospitals in the we're
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  surrounded by health systems,
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  which are multi multi hospital systems, and we're
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  we're a stand alone,
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  in a in a sea of giants in
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  terms of financial size. Yeah. Okay.
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  How do you how how does that work?
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  I mean, how do how do you stand
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  out? How do you how do you compete?
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  We compete
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  in a number of ways. We believe that
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  we have to have high patient satisfaction,
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  very high quality,
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  at a much lower cost, and we compete
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  well on all three of those. For instance,
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  we're a magnet for nursing. Magnet hospital, CISMAGNET
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  was created,
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  leapfrog a. We've been leapfrog a, I think,
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  10 of the last 13 cycles and and
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  many in a row.
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  So we have,
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  and patient satisfaction. We're the number one
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  last ten years for most likely to recommend.
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  So we have high high quality, high patient
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  satisfaction,
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  and our financial performance, our balance sheet is
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  now stronger than it's ever been in as
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  a hundred and seventeen years.
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  Okay. I'm looking forward to digging more into
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  into that as we talk. Let's start by
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  talking, if we can, a bit about technology
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  and how a health system like yours uses
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  technology.
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  In particular, I'm interested in the adoption of
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  AI. Of course, everybody is. Right? But one
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  thing I'm interested in is, like, health care
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  has,
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  often moved rather cautiously
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  when it comes to technology investment.
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  Is that still true? Is AI changing that?
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  Like, how how do you see that? Well,
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  we have a governance structure,
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  but in particular, it has to have an
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  ROI.
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  There are many things that that,
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  AI can do for us.
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  But is it really going to change the
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  needle? If it doesn't change a needle from
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  a performance standpoint, it's kind of hard to
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  justify. That doesn't mean there aren't things that
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  we can do.
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  It depends on the investment value. You know,
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  if it's a relatively small investment, then we'll
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  probably do it. But if it's a large
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  investment, it's got to have an ROI to
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  it. And we are doing things in in
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  in the revenue cycle that I think are
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  a little unique.
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  It happens to be we started a project
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  a few years ago using
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  partnering with a company to do AI
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  on,
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  getting patients enrolled in Medicaid. We're a safety
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  net hospital. 25% of our patients are on
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  Medicaid.
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  And in the state of New Jersey, I
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  don't know about other states, but state of
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  New Jersey, when you're on general assistance, which
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  means Medicaid,
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  you're entitled to Medicaid, but you're not on
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  Medicaid.
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  You have to have a medical incident in
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  order to get on Medicaid. So you usually
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  have to wind up in an emergency room
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  or in a a FQHC, fairly qualified health
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  center, or our family health center, and we
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  start the enrollment process. Used to be a
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  manual process, and you have to put a
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  presumptive eligibility form in to say, okay. We
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  think this patient qualifies, and then if we
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  ever actually do get Medicaid, it'll be retroactive
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  to that date and get paid. Well, the
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  new
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  big beautiful bill shut those those presumptive eligibility
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  times from ninety days to thirty days starting
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  next year. And then,
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  redeterminations
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  used to have a year of Medicaid. Now
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  it's every six months you have to reenroll.
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  So we work with a company for AI
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  in order instead of trying to get them
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  to come back with all their information. No
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  one walks in the door for all the
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  information they need to enroll in Medicaid or
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  charity care. We also do it for charity
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  care too. Yeah. So we we but most
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  of them have smartphones.
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  So we have an app put on their
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  phone, and we teach them how to, when
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  they get home, how to image the documents.
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  Mhmm. That will automatically goes into the, into
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  the platform.
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  It determines automatically whether it goes into the
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  Medicaid bucket or it goes into the charity
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  care bucket and completes the application, automatically sends
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  it on to Medicaid.
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  So we're able to get most of our
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  applications,
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  implemented
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  within thirty days, which is what the new
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  law is gonna require. If it goes beyond
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  that, you won't get you'll get Medicaid going
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  forward, but you won't get it retroactive to
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  that date. Right. Right. Excellent. That's a really
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  nice example. And you mentioned,
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  you mentioned some of the levers or the
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  the the differentiators, right, that that
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  you,
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  that are important to you, patient satisfaction and
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  efficiency and so on. And and you've just
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  given a really nice example.
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  Where where
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  like, when you think about this new technology,
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  which of those dimensions of your differentiation is
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  it going to best support, do you think,
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  as you look at ROI?
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  I think it's be across the board. I
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  I I want to
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  implement it in many ways in the revenue
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  cycle. Okay. That's, I mean, it's one of
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  my purviews. Sure. But I can see it
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  in many, many clinical applications. I was just
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  at a at a presentation early today, where
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  an organization was using it for presumptive
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  elements of trying to predict
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  a patient
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  who could gonna go south within a certain
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  number of hours because of their current parameters,
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  and they're able to
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  to intervene before
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  a negative,
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  medical event happens.
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  That's a great use of AI technology and
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  one that you may may or may not
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  have the direct ROI. But if you have
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  something like that, it will certainly improve your
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  outcomes,
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  which also goes to,
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  patient satisfaction. Patient satisfaction.
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  Exactly.
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  And word-of-mouth still carries the the day in
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  many ways in terms of of getting your
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  word out. You're a high quality, low cost
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  facility. Yeah. Okay. Let's talk talk about the
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  revenue cycle. You you you you you brought
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  it up. It it revenue cycle has been
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  one of those areas for years that's been
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  very labor
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  centric in its approach. Right? Technology's been a
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  sort of copilot, a partner rather than the
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  the prime,
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  axis of of revenue cycle work. And it
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  it feels like that is changing with AI
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  and its ability to,
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  code more accurately potentially and reduce errors and
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  potentially reduce some friction Yeah. With the payer
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  community.
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  How did how do you see that?
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  It still needs more people, and I'll give
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  you an example. So back, prior to the
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  pandemic,
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  we had a denial rate that was around
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  a little under two percent.
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  And then during the pandemic,
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  a lot of the payers,
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  eased up on the review process because of
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  the obviously, because of the issues related to
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  pandemic, and that we appreciated that. But somewhere
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  in '22, about midyear,
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  seemed like all the payers went to some
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  conference and figured, how do we go ahead
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  and screw hospitals out of money? And the
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  denial rates absolutely shot through the roof. So
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  the '22
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  into '23.
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  Oh. So we had a great revenue cycle.
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  We had an independent company come in and
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  look at our revenue cycle. This is before
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  the pandemic and said, they had little tweaks
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  that we can improve. Nobody has the perfect
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  revenue cycle. And so we had some small
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  things to improve, but nothing major. And, we
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  really had a, like, a clean bill of
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  health. And now denials were off the shore
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  off the charts. We had to retool.
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  We had to rethink the entire process. We
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  went up to, like, 10%
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  denials
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  from under two.
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  So we invested. We looked at the processes
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  we had to do, so we added more
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  utilization
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  review nurses. We beefed up our physician advisers.
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  We included new technology on the back end
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  for monitoring and being able to predict trends
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  on where where denials were going. We improved
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  people in the back end actually managing denials
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  to make sure that we got them all
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  because they don't all come in from one
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  source. Everybody believes in eight thirty five, which
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  is electronic transfer of data which goes with
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  your claim being payment.
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  That's not where all the dials come from.
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  They come from other sources in many different
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  ways. So we had to find ways to
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  get the full picture and then be able
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  to address it by payers. And we had
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  to improve include our managed care people into
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  the process when we had claims.
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  Just in this year, earlier in 2025,
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  we settled with a payer on claims for
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  2022 and prior. These were all claims that
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  were denied for various reasons, and
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  they have but were not justified. Mhmm. And
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  we settled for millions of dollars on them.
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  So because we don't give up on anything.
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  That's another thing. We don't we don't give
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  up on anything we think we're entitled to.
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  Mhmm. Mhmm. So,
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  so we've retooled the whole thing. So I
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  just did a presentation for our finance committee
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  showing that now our denial rates,
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  on a quarterly basis is about net of
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  denials net of recoveries is about two and
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  a half percent. So we're getting close to
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  the pre pandemic
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  period of
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  time. And I don't know if too many
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  places have gotten to that level yet. Mhmm.
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  It shows that it's really
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  improved. And another thing that we've done is
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  we looked at
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  physician advisors and what they were doing. So
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  we have
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  we have,
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  women and children, so neonatology,
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  we have pediatric
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  PICU. So when we have denials in the
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  NICU or in the PICU,
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  we don't have our regular physician advisors fighting
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  the claim on a peer to peer basis.
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  We'll have a neonatologist
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  do it. Got it. Or a pediatric intensivist
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  do it, or a women to the maternal
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  fetal medicine doctor.
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  Because the payers use mostly primary care doctors
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  for utilization management on their side. Yeah. And
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  so we have a it's almost like a
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  boxing match. We'll have a heavyweight,
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  a neonatologist
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  a specialist. A specialist go up against the
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  primary care doctor, and nothing against primary care
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  doctors. They're very, very good, but it's not
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  their specialty. Sure. So our specialists can really,
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  in all intents and purposes, run rings around
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  Right. Primary care doctors with the clinical expertise
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  that they have. And and so with so
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  our peer to peer turnover rate was about
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  35%.
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  Now we just hit 80% in the last
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  quarter. Okay. So And and is that does
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  that come with I mean, do they have
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  time to do that? Like, how do you
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  deal with the there's a some administrative
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  burden that comes with that. Right? Well, we
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  don't do it all the time. It's only
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  on select cases. Right. That we and we've
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  done it in other areas. We have a
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  nationally renowned geneticist. We've had denial
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  of some of the of the,
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  clinical care on on genetics patients. And the
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  average genetics patients, the drug cost is about
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  $400,000
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  a year. Right. And we're having some of
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  the those drug and they're infused, so they
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  come to the hospital for infusions.
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  Having some of that denied or or that
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  cutback on the on the therapy being given,
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  I'm like, are you kidding me? Patient on
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  genetics, if you don't have that medication,
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  you may not be around much longer. Right.
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  So, so we use the we use specialists
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  in certain areas in order to,
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  win the day in terms of, clinical judgment.
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  What about the patient interface? How are you
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  using technology or new technologies there to help
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  you manage the patient relationship? I suppose you
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  gave a nice example about charity and, Medicare
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  enrollment earlier on. Are there other things that
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  you're doing? Well, we we have other things
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  we wanted to do, but right now we're
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  in the middle of installing Epic.
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  So I can't do
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  you can't put too many things on an
• 13:05
  organization at once. So if you're installing Embic,
• 13:08
  which is all hands on deck type of
• 13:10
  implementation,
• 13:11
  you can't really start doing other initiatives.
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  We had,
• 13:15
  some robotic learning we were planning on on
• 13:18
  terms of insurance verification work. And I think
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  over the next five years, we'll probably have
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  25 to 30% of our revenue cycle
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  in automation and be both AI and just
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  regular robotic learning. Yeah. Yeah. Yeah. Yeah. And
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  you mentioned let's just maybe as we as
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  we bring it to a conclusion, let's circle
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  back to a comment you made about the
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  relationship of people and technology and finance and
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  in revenue cycle. And you were saying that,
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  you know, we need more people.
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  Yeah. So we're talking about widespread automation, but
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  we're also talking about the role of people.
• 13:51
  Yeah. How how does how does that people
• 13:53
  part change?
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  It will reduce. I don't expect to lose
• 13:58
  anybody
• 13:59
  because of of automation and AI.
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  I expect to redeploy them Yeah. In other
• 14:05
  in other roles. Mhmm. So we will probably
• 14:08
  through attrition, we'll probably, reduce the workforce, but
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  I don't wanna see people losing their jobs
• 14:12
  because of automation.
• 14:14
  I don't even know if auto AI is
• 14:16
  going to be the long term solution for
• 14:19
  everything,
• 14:20
  because if you look at the cost right
• 14:22
  now on AI, it's gonna be somewhat prohibitive
• 14:26
  at some point in time.
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  And, if I was an investor,
• 14:30
  right now, I wouldn't even invest in AI
• 14:32
  because I think it's overvalued.
• 14:34
  But but I do believe it has many
• 14:36
  good uses.
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  But it's like anything else. It's there has
• 14:40
  to be monitored by people. They will have
• 14:43
  to see how that technology because technology can
• 14:46
  go awry.
• 14:47
  Now you look at some of the things
• 14:48
  that have been done with AI and you
• 14:50
  suddenly realize that they
• 14:52
  chat GPT sometimes gives you the wrong conclusion.
• 14:55
  It does. It's not and so it's it's
• 14:57
  not exactly a perfect science. Right. It's a
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  science that has it's a tool.
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  I look at it as a tool,
• 15:04
  as one of the many tools. And sometimes
• 15:06
  the tool may what makes me be better
• 15:08
  than people, and sometimes the people may be
• 15:10
  better than the tool. Yeah. Very good. Anything
• 15:13
  else, Garik, on your mind as we, as
• 15:16
  we conclude?
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  I've got a lot of other things. I
• 15:19
  mean, the big beautiful Yeah. The big beautiful
• 15:21
  bill had really caused,
• 15:22
  a lot. I mean,
• 15:24
  we started to rethink about how we have
• 15:26
  to improve our operations because of the denial
• 15:28
  hits that happened in '22. And so Yeah.
• 15:31
  We've been on what we call a performance
• 15:32
  excellence. We took eight different areas of the
• 15:35
  hospital, workforce,
• 15:37
  length of stay,
• 15:39
  turnover times in the OR,
• 15:43
  improving access to having lower no show rates,
• 15:46
  and
• 15:47
  and being able to see patients
• 15:49
  as fast as possible. We have a we're
• 15:51
  a children's hospital, so we have all the
• 15:53
  pediatric subspecialists. And if you know anything about
• 15:55
  pediatrics,
• 15:56
  they're nowhere near enough specialists. The average wait
• 15:58
  time for specialists is three to six months,
• 16:01
  in some cases, even longer.
• 16:02
  So we're looking at improving that access
• 16:05
  across the board, not just in pediatrics, but
• 16:08
  so we have this performance excellence to improve
• 16:10
  our operations. We know our margins are gonna
• 16:13
  get hit
• 16:14
  as the as the big bill. And so
• 16:16
  many places are looking at it now because
• 16:18
  of the big bill. We were doing because
• 16:19
  of denial. So we're ahead of a lot
• 16:20
  of people Mhmm. In terms of improving our
• 16:22
  operating results. Like I said, we have we're
• 16:24
  very strong right now. We wanna keep it
• 16:26
  that way. The hospital association in in New
• 16:30
  Jersey modeled
• 16:31
  the impact of the big beautiful bill, and
• 16:33
  it says that if you aggregate all the
• 16:35
  hospitals up bottom lines over the next seven
• 16:38
  years, we're gonna lose two thirds of that
• 16:40
  margin
• 16:42
  if if nothing else changes. And that's a
• 16:44
  static analysis, so it doesn't take into account
• 16:46
  volume changes and other operating. But if we
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  just did nothing,
• 16:50
  two thirds of that margin goes away. If
• 16:51
  the hospitals in the country right now don't
• 16:53
  make money. Mhmm. So think about this across
• 16:56
  the country. It's it's gonna be have an
• 16:58
  enormous impact.
• 16:59
  Yeah. Right. Right. If you're not changing your
• 17:02
  operations now,
• 17:03
  then, you're gonna be in in serious,
• 17:06
  world of hurt.
• 17:09
  A salutary,
• 17:11
  way to end, Gary. Thank you very much
• 17:13
  for sharing your thoughts and time with us
• 17:15
  today. Thank you very much. Thank you for
• 17:17
  having me. Thanks.