Latest / Becker’s Healthcare Podcast / Trust by Design: How Voluntary Accreditation is Shaping Responsible Healthcare AI

Transcript

Trust by Design: How Voluntary Accreditation is Shaping Responsible Healthcare AI · Becker’s Healthcare Podcast

• 0:00
  Hi, everyone. This is Lucas Voss with Becker's
• 0:02
  Healthcare. Thanks so much for tuning in to
• 0:03
  the Becker's Healthcare podcast series. It's fantastic to
• 0:06
  have you. Today, we're talking about how voluntary
• 0:09
  accreditation
• 0:10
  is shaping
• 0:11
  responsible health care AI, and I'm so excited
• 0:14
  to welcome doctor Sean Griffin. He's the CEO
• 0:17
  of Eurac. You know, his career spans clinical
• 0:19
  practice, MOC, group leadership, and innovation in care
• 0:21
  delivery. After years of practice, doctor Griffin stepped
• 0:24
  into that CEO role to broaden his impact,
• 0:27
  bringing his experience beyond the exam room to
• 0:29
  help advance quality, accountability, and innovation across the
• 0:32
  country and the world. At York, he focuses
• 0:34
  on strengthening and evolving accreditation programs, influencing policy
• 0:38
  in and building a culture that supports both
• 0:40
  high standards
• 0:42
  and meaningful growth for his team. Doctor Griffin,
• 0:45
  I'm so excited to have you. Welcome to
• 0:46
  the podcast.
• 0:47
  Thank you very much, Lucas. I'm looking forward
• 0:49
  to this discussion.
• 0:50
  Yes. We have lots to talk about.
• 0:53
  AI is being adopted very rapidly,
• 0:56
  across many different disciplines, clinical administrative,
• 0:59
  pace patient facing workflows.
• 1:02
  But a lot of leaders, even though it's
• 1:03
  being adopted, are saying they're unsure how to
• 1:05
  evaluate risk, transparency,
• 1:07
  accountability,
• 1:08
  a lot of different factors.
• 1:10
  What gap did you see in the market,
• 1:12
  and how does the Healthcare AI accreditation address
• 1:15
  that specific need?
• 1:17
  Well, I'm fortunate in that I was a
• 1:19
  chief medical information officer for a couple decades
• 1:21
  back when I was in clinical practice and
• 1:23
  working as part of health systems.
• 1:24
  And when you're a CMIO,
• 1:27
  you get used to technology rolling in and
• 1:29
  you have rollout plans and training plans and
• 1:31
  all those sort of things.
• 1:33
  And AI really is
• 1:35
  similar to some of those things, but it's
• 1:37
  different also. And so what we were looking
• 1:39
  at is we're we're very involved in the
• 1:41
  policy, level in Washington, DC and in in
• 1:43
  guiding policy. You know, we've been around for
• 1:46
  three and a half decades. We do all
• 1:47
  this work in quality.
• 1:48
  And what I was seeing was I was
• 1:50
  seeing this come in,
• 1:51
  into healthcare. And actually, I spoke on AI
• 1:54
  in healthcare back in 2018
• 1:56
  to a bunch of chief medical information officers
• 1:58
  who were were early on in their careers.
• 2:00
  And back in 2018,
• 2:01
  it was mainly being done with PowerPoint slides
• 2:04
  because there really wasn't much meat underneath those
• 2:06
  PowerPoint slides. It was being used for funding
• 2:08
  and talk about, you know, sort of robot
• 2:10
  maids and flying cars and AI and healthcare.
• 2:13
  But over the past few years, what we
• 2:15
  saw was we saw that there was more
• 2:17
  of this rolling in and it was being
• 2:19
  being sold. And if you went to a
• 2:20
  a big technology and healthcare
• 2:22
  sort of meeting, the vendors were switching over
• 2:25
  from being EMR vendors to being AI vendors.
• 2:27
  And AI was in everything. It was the
• 2:29
  sprinkles on top of every piece of technology.
• 2:31
  They're talking more and more about AI.
• 2:33
  And what I was hearing from my my
• 2:35
  friends who are still in practice in the
• 2:36
  organizations that we work with was
• 2:39
  we we need some guardrails on this, that
• 2:41
  this is moving faster than regulation is keeping
• 2:43
  up, and we can't tell the good guys
• 2:46
  from the bad guys.
• 2:47
  And, accreditation
• 2:49
  has a history of helping you tell the
• 2:50
  good guys from the bad guys. I describe
• 2:53
  accreditation as like being a quality auditor.
• 2:55
  We we we step in and we say
• 2:57
  we're gonna check behind the scenes and we're
• 2:59
  gonna tell you that they're doing things right.
• 3:01
  And not just the, oh, they say they're
• 3:03
  doing it right, but we're actually gonna make
• 3:04
  sure that they're doing it right. And so,
• 3:07
  we went to our board, and our board
• 3:08
  is a mix of stakeholders, everything from doctors
• 3:11
  to nurses to health plans to pharmacies
• 3:14
  to all these different groups. And we said,
• 3:16
  we're very concerned about this technology outrunning the
• 3:18
  rules
• 3:19
  and putting both patients and providers in a
• 3:22
  dangerous place where they don't know,
• 3:24
  what to trust. They're not trained on it.
• 3:26
  They don't understand the risk.
• 3:29
  And honestly, we saw some bad actors who
• 3:31
  were coming to the table with tools that
• 3:33
  weren't fully baked and weren't trustworthy.
• 3:36
  And so we said, you know, we think
• 3:38
  this needs some independent oversight.
• 3:41
  We looked at what was going on, and
• 3:42
  honestly, there's 200 best practices out there,
• 3:46
  and best practice organizations and recommendations and all
• 3:49
  these sort of things. And oddly enough, they
• 3:50
  don't all agree on anything.
• 3:52
  But we said is is best practices saying
• 3:54
  you're following best practices
• 3:56
  is like saying you're gonna make a New
• 3:58
  Year's resolution. It's like, we're we're gonna do
• 4:00
  our best. And it's like, you know, in
• 4:01
  in in health care, just doing our best
• 4:03
  has never been good enough. So we said,
• 4:06
  we're willing to take
• 4:07
  our reputation and our integrity that we've built
• 4:10
  over decades
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  and and step into this space.
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  So, we we we built a program. We
• 4:15
  we got stakeholders, an open call for stakeholders
• 4:18
  to come together.
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  And, we had some great minds around around,
• 4:22
  the table contributing to this. We had academic
• 4:25
  medical centers. We had practicing physicians. We had
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  lawyers.
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  We had ethicists.
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  We had,
• 4:31
  pharmaceutical
• 4:32
  companies.
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  And when we got them together, we were
• 4:35
  planning on doing a program around users of
• 4:38
  AI. So an accreditation program to protect the
• 4:40
  users of AI.
• 4:42
  And when we got that group together,
• 4:44
  they said, well, yes. We need that. We
• 4:46
  desperately need that. There there are no regulations
• 4:49
  right now guiding this on a a national
• 4:50
  basis.
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  But we also need one for the developers
• 4:54
  because
• 4:55
  we're looking at the developers and we can't
• 4:57
  tell whether they know what they're doing or
• 4:58
  not before they start trying to sell to
• 5:00
  us. And so they were sort of looking
• 5:02
  for, can somebody check behind the scenes before
• 5:04
  it even shows up at our door,
• 5:06
  to to make sure that the vendors are
• 5:08
  doing it right? So that's what we stepped
• 5:10
  into. We developed that program. We rolled it
• 5:12
  out last year. It's the first
• 5:14
  AI and health care accreditation program.
• 5:16
  It's designed one module for users, one module
• 5:19
  for developers,
• 5:20
  and it's been very positively responded to. It
• 5:23
  took off faster than any program we've launched
• 5:25
  in about the seven years I've been here,
• 5:27
  and we've got good feedback on it. We've
• 5:29
  got regulators who want to know more about
• 5:30
  it because they're looking at how they can
• 5:32
  approach it. We've got big healthcare organizations who
• 5:35
  are looking at it because they're like, we're
• 5:37
  we're tired of just saying we're following best
• 5:39
  practice. We think this needs to be verified
• 5:41
  and trustworthy.
• 5:42
  And we're hearing from from users who are
• 5:44
  like, you know, all of a sudden I've
• 5:45
  got this AI tool which has been stuffed
• 5:47
  into my EMR. I had no training on
• 5:49
  it. I don't know about the data privacy.
• 5:52
  We hear all these horror stories about risk
• 5:54
  and bias and hallucinations
• 5:56
  and those sort of things. And so, we
• 5:58
  just we wanted to put some guardrails up,
• 6:00
  and that's what our program is.
• 6:03
  How do those standards then if you wanna
• 6:04
  talk a little bit about some of those
• 6:06
  core pillars, right, of the program in itself,
• 6:08
  and then you you just mentioned some of
• 6:10
  those standards involve just an individual looking at,
• 6:12
  okay, how am I actually
• 6:14
  using AI on a daily basis? But how
• 6:16
  do those standards then translate
• 6:18
  into those safeguards in practice, both clinically and
• 6:21
  operationally?
• 6:22
  Okay. Well, in any program that we do,
• 6:24
  and we have over 40 different programs that
• 6:26
  we do in healthcare, there are some things
• 6:28
  we call the foundational focus areas. Foundational focus
• 6:30
  areas are sort of those core quality
• 6:33
  structures that any organization should have if it's
• 6:35
  going to be in healthcare. It's things like
• 6:37
  regulatory compliance,
• 6:39
  regulatory monitoring. When the laws change, are you
• 6:42
  going to catch those things? It's about
• 6:44
  statements of work, contracting,
• 6:47
  data protection,
• 6:48
  privacy protection.
• 6:50
  We actually,
• 6:52
  scalability.
• 6:52
  You know, I'd hate to deploy a tool
• 6:54
  into my system that that couldn't keep up
• 6:57
  with growth. You know, I I don't wanna
• 6:58
  have a server crash and all of a
• 7:00
  sudden my doctors can't get recommendations for what
• 7:02
  they should be doing, those sort of
• 7:04
  things. So we we have those sort of
• 7:06
  foundational focus areas. Are the people who are
• 7:08
  doing it qualified to do it?
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  Things that just make common sense, but we
• 7:12
  actually check those things because we say you
• 7:14
  can't assume those things are being checked.
• 7:16
  A code of ethical conduct for both the
• 7:19
  developers and the users. Have they actually looked
• 7:21
  at this from an ethical standpoint?
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  Have they looked at it from a technical
• 7:24
  standpoint? Have they looked at it from a
• 7:26
  clinical standpoint?
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  Sadly enough, there are some AI tools which
• 7:29
  are being rolled out which really don't have
• 7:31
  clinicians involved in their development.
• 7:33
  So I've heard of physicians who say, I
• 7:35
  just got given this new tool to use
• 7:37
  for patient email responses and it doesn't have
• 7:40
  a medical
• 7:41
  dictionary
• 7:42
  to make sure that the words are the
• 7:43
  right words that are supposed to be used.
• 7:45
  It has a technical dictionary, but not a
• 7:47
  medical dictionary.
• 7:48
  And that's just a case of, you know,
• 7:50
  where things may work great over in finance,
• 7:53
  but when you're going to bring them into
• 7:54
  the clinical world, we actually have a higher
• 7:56
  standard that we expect people to follow.
• 7:59
  So so we have all those foundational focus
• 8:01
  areas, which which go into either program, whether
• 8:03
  a user or a developer.
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  And and be honest, there's some organizations that
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  are doing both. I mean, I've heard of
• 8:08
  big hospital systems where they say they have
• 8:10
  over a thousand AI tools that they're deploying.
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  And if if we said they have a
• 8:14
  thousand drugs that they're developing and using on
• 8:16
  patients, we'd go, maybe somebody outside the organization
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  needs to be looking at these things.
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  But, in AI, you can have, you know,
• 8:23
  six guys in a garage write a bunch
• 8:25
  of code, and all of a sudden you
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  have a tool that'll be showing up at
• 8:27
  your your next vendor
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  fair. Yeah. Absolutely.
• 8:31
  And, again, we know that part of the
• 8:32
  issue as you've mentioned before, there there's not
• 8:34
  a lot of regulation
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  around it. No. The the garage guys can
• 8:39
  develop their tool, bring it to market, and
• 8:41
  then effectively sell it to health care. Right?
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  That's a part of the process right now.
• 8:46
  How does then voluntary accreditation differ from regulation
• 8:51
  in the context of health care AI? And
• 8:53
  why is that
• 8:54
  distinction so important, especially now
• 8:57
  when we have the guys in the garage
• 8:59
  developing these AI tools? Yeah. So so AI
• 9:03
  under the previous administration, AI was had some
• 9:06
  constraints on it.
• 9:07
  There were some regulatory frameworks that were being
• 9:09
  thrown around
• 9:11
  at the federal level. And when we looked
• 9:12
  at that, we're like, okay, there are some
• 9:14
  guardrails that are being applied.
• 9:16
  And with the most recent change in the
• 9:18
  White House, they said we're concerned about holding
• 9:21
  AI back too much. And so they they
• 9:23
  suspended some of those executive orders and some
• 9:25
  of those rules.
• 9:26
  And whether those rules were great rules or
• 9:28
  terrible rules, they suspended those rules. And so
• 9:31
  now you've got sort of this vacuum at
• 9:32
  the federal level as to what are the
• 9:35
  rules going to be. You have states where
• 9:37
  they have, you're developing a patchwork of states
• 9:40
  where maybe Colorado is concerned about this and
• 9:42
  California is concerned about this. And my old
• 9:45
  home state of Iowa may not have any
• 9:47
  rules whatsoever.
• 9:48
  But if you're a developer, how do you
• 9:50
  sell into those markets when not every facility,
• 9:54
  respects state lines?
• 9:55
  When I used to practice, I was in
• 9:57
  St. Joseph, Missouri. And in St. Joe, I
• 9:59
  had patients who were from Kansas, from Missouri,
• 10:01
  from Iowa, from Nebraska.
• 10:03
  And it's really strange to think, well, wait
• 10:05
  a minute. They're from Iowa, so I can
• 10:06
  use this email tool,
• 10:09
  but their cousin is from Missouri. And so
• 10:11
  for their chemotherapy, I can't use this tool.
• 10:14
  And and that's not how medicine has tended
• 10:16
  to work. And so we looked at the
• 10:17
  regulations. I mean, you're still supposed to follow
• 10:20
  HIPAA. HIPAA has been around for a while.
• 10:22
  But the thing about AI is that AI
• 10:25
  changes.
• 10:26
  And so there are some particulars that can
• 10:29
  change when you're talking about an AI deployment.
• 10:32
  And what we say is it's really sad
• 10:34
  to think about it, but right now there's
• 10:35
  actually more regulatory oversight for the hospital cafeteria
• 10:39
  than there is for the hospital AI program.
• 10:43
  Absolutely. And again,
• 10:45
  the I think it's partially also because
• 10:47
  the word regulation comes with a lot of
• 10:50
  stigma around it, specifically for folks that want
• 10:52
  to move fast and that are we have
• 10:54
  to be cutting edge. We have to drive
• 10:57
  innovation
• 10:58
  across the enterprise. And then you say, oh,
• 11:00
  wait. Regulation.
• 11:02
  And that's it's a worry for a lot
• 11:04
  of folks. Again, that it slows innovation and
• 11:06
  adds friction in the
• 11:07
  AI process within an organization.
• 11:10
  From what you're seeing though, how can those
• 11:12
  responsible AI frame frameworks actually accelerate this process
• 11:16
  and help organizations
• 11:18
  then
• 11:19
  scale
• 11:20
  AI safely?
• 11:21
  Well, I I would say if if you
• 11:23
  look at f one drivers
• 11:24
  doing over 200 miles an hour in a
• 11:26
  car, they do wear a seat belt.
• 11:29
  You know, you you actually need some controls
• 11:32
  if you're gonna go fast.
• 11:34
  And when I think about regulation,
• 11:36
  the nice thing about accreditation is accreditation has
• 11:39
  been around for decades and accreditation
• 11:41
  actually has the ability to change and move
• 11:43
  along with a rapidly changing
• 11:46
  care environment.
• 11:48
  So, whereas I'll tell you right now in
• 11:50
  Washington, DC, it's difficult to pass any laws.
• 11:53
  There's just so much so many, so much
• 11:55
  tug of war going on in DC.
• 11:57
  But accreditation
• 11:58
  being voluntary,
• 12:00
  right now accreditation is being approached by people
• 12:03
  who say, we recognize there needs to be
• 12:05
  some other oversight on this, and we're gonna
• 12:07
  go for that. For my generation, it'd be
• 12:10
  the good housekeeping seal of approval. You know,
• 12:12
  for younger generations, gonna go for those Yelp
• 12:14
  reviews or whatever it is. But some somebody
• 12:16
  needs to be reviewing the safety and the
• 12:19
  efficacy
• 12:20
  of what's going on in health care AI
• 12:22
  in particular. We're not putting out an accreditation
• 12:24
  program for your bank's AI. We're saying health
• 12:27
  care is a different,
• 12:29
  different beast and it needs it needs a
• 12:31
  little bit of a collar at least so
• 12:33
  that people feel they can come and pet
• 12:35
  it.
• 12:36
  And it touches so many different people. We
• 12:39
  all are involved in health care. That's part
• 12:41
  of our lives. We have to be able
• 12:44
  to say, okay, there is regulation. There are
• 12:46
  some guardrails. There is that collar as you've
• 12:47
  mentioned to be able to control some of
• 12:49
  this. Yeah. I I do wanna come back
• 12:51
  to the the guys in the garage a
• 12:52
  little bit here because, again, it's I think
• 12:54
  it's an it's an important part of the
• 12:56
  conversation.
• 12:57
  Looking ahead, as we head into the rest
• 12:59
  of 2026
• 13:00
  and certainly
• 13:01
  beyond,
• 13:02
  how do you expect accreditation to influence that
• 13:05
  vendor selection and then also the competitive positioning
• 13:08
  and just in general the overall trust
• 13:11
  in health care AI?
• 13:13
  I I think there's a couple different places
• 13:15
  where where this can come in.
• 13:17
  I will tell you I've talked with hundreds
• 13:19
  of organizations
• 13:20
  and some of them have a very good
• 13:23
  governance and adoption framework that they use for
• 13:26
  their organization
• 13:27
  for any technology coming in. I actually used
• 13:29
  to chair the technology adoption committee at my
• 13:32
  hospital system,
• 13:33
  and so I'm familiar with that. And if
• 13:35
  you're going to buy a new CT scanner,
• 13:37
  one of the things that you do is
• 13:38
  you look at, you know, what's it to
• 13:40
  be used for, you know, who developed it,
• 13:42
  are they going to be in business next
• 13:43
  year, And then how do we bring it
• 13:45
  in? How do we train on it? Do
• 13:46
  we have the electrical hookups? Are our systems
• 13:48
  ready for it? And and and what's it
• 13:50
  going to do for us? And so I
• 13:53
  I think that what we're hearing is that
• 13:55
  people who are looking at vendors coming in
• 13:57
  from the outside
• 13:58
  have said, we really think that we should
• 14:00
  start writing in this idea of an accreditation
• 14:03
  for vendors before we will consider them as
• 14:05
  being part of the process.
• 14:07
  You know, it's sort of like a you
• 14:08
  know, if it's four guys in a garage,
• 14:11
  they could go out of business next week
• 14:12
  or mom could kick them out of the
• 14:14
  garage and then they suddenly don't even have
• 14:15
  an office.
• 14:16
  And so when it comes to AI tools,
• 14:18
  especially anything that influences
• 14:21
  patient care,
• 14:22
  patient care has always been a special trusted
• 14:25
  area. You know, we talk about evidence based
• 14:27
  medicine and and what's the research show and
• 14:29
  those sort of things. And AI is breaking
• 14:32
  some of those rules. And not only is
• 14:34
  it breaking some of those rules when it
• 14:35
  shows up, it's breaking some of those rules
• 14:37
  a week later when it might have changed
• 14:39
  a little bit. So for example, when we
• 14:41
  talk about AI programs, we say before you
• 14:44
  adopt an AI program, you should analyze it
• 14:46
  from a risk standpoint.
• 14:47
  What is the risk of the usage of
• 14:49
  this tool?
• 14:50
  If it's high risk, you have to keep
• 14:52
  a closer eye on it. If it's low
• 14:54
  risk,
• 14:55
  you know, you can you can check it
• 14:56
  every month or so, something like that, if
• 14:58
  it's not affecting patient care.
• 15:00
  Just to illustrate that point, one of the
• 15:02
  analogies that I use is think of anything
• 15:05
  you're asking AI to do in health care
• 15:07
  and imagine it's a person doing the same
• 15:09
  thing.
• 15:10
  Okay? So
• 15:12
  if if you went into the doctor's office
• 15:13
  today and they said,
• 15:15
  Larry, is going to come into the office
• 15:18
  into the exam room with you and he's
• 15:20
  going to write down everything that we say
• 15:21
  so that I don't have to write it
• 15:22
  all down. Are you okay with that?
• 15:24
  Well, it's a very natural question to say,
• 15:26
  well, who's Larry? You know, what's Larry's background?
• 15:29
  Was Larry, you know, picking up the recycling
• 15:31
  earlier today and he just happened to wander
• 15:33
  by, but he's got really nice handwriting, so
• 15:35
  this is fine? So so there's a credentialing
• 15:37
  analogy here for when you bring something into
• 15:40
  your system, is it trained? Is it qualified?
• 15:43
  Is it doing the job that you expect?
• 15:44
  And who's gonna keep an eye on it
• 15:46
  until you trust it?
• 15:48
  And we're saying the same things for AI.
• 15:50
  Our accreditation
• 15:51
  standards are actually out there on the web.
• 15:53
  You could look them up. You could go
• 15:55
  to our website, eurec.org.
• 15:57
  You could see what our standards are, what
• 15:58
  they talk about. And that gives you a
• 16:00
  really nice framework for what you should look
• 16:03
  for both in from your developers and also
• 16:05
  in your deployment.
• 16:07
  Now, the next step is,
• 16:09
  okay, we say we're gonna follow those things,
• 16:12
  but patients don't know to trust us. You
• 16:14
  know, providers don't know to trust us. They
• 16:16
  don't wanna be hung out to dry with
• 16:18
  liability from some tool that's not all the
• 16:20
  way baked or is the the four guys
• 16:22
  in the garage who developed it. The other
• 16:24
  thing is is that
• 16:25
  are we training as we roll these things
• 16:27
  out? I know that some of the the
• 16:28
  AI scribes have been rolled out to hundreds
• 16:32
  of thousands of users,
• 16:33
  and I'm not familiar with how much training
• 16:36
  they're getting on on those tools.
• 16:39
  Some organizations are doing a great job with
• 16:40
  it. Others are sort of like, oh, we
• 16:42
  put a new AI scribe into the EMR
• 16:44
  today. We want you to take a look
• 16:46
  at the notes and and, and use those
• 16:48
  for your notes going forward. And that's that's
• 16:50
  really not how we have done things when
• 16:52
  it comes to this. And and there's risks
• 16:54
  that pop up. There's there's horror stories of
• 16:56
  just terrible things. But there's also you know,
• 16:59
  I'm hearing from doctors these tools have been
• 17:01
  rolled out. And, yes, they're letting me pay
• 17:03
  attention to the patient in the exam room.
• 17:05
  But then that means after the exam room,
• 17:07
  I have to go read through all of
• 17:09
  the notes and make sure they got it
• 17:11
  right.
• 17:12
  Because a mistake in the record, it can
• 17:14
  be damaging to the patient in in ways
• 17:16
  you don't expect.
• 17:18
  Yeah. Well, doctor Griffin, I feel like we
• 17:20
  could talk for another hour. There's so much
• 17:22
  to as you've mentioned, there there's so much
• 17:24
  to talk about and and so many different
• 17:26
  aspects to this conversation. I wanna thank you
• 17:28
  for your time and for your insights. This
• 17:29
  was fantastic. Thanks for being here.
• 17:32
  Well, I appreciate the opportunity to talk a
• 17:33
  little bit about this, but, you know, take
• 17:35
  a look at our website. There will be
• 17:37
  other,
• 17:37
  AI programs that'll probably come out. We'll update
• 17:40
  this as need be, but, it's a it's
• 17:42
  a very sensitive area, and we're just offering
• 17:44
  to, to help organizations
• 17:46
  to to do it right to protect their
• 17:48
  patients and their providers. So thanks very much,
• 17:49
  Lucas. Absolutely. It's great to have you. At
• 17:51
  least talk to the guys in the garage.
• 17:53
  Don't just buy their product.
• 17:55
  Yes.
• 17:56
  The the guys in the garage,
• 17:58
  may may not be that much smarter,
• 18:00
  and you're you're you're letting risk into your
• 18:01
  organization if you don't check them out. Exactly.
• 18:04
  Well, doctor Griffin, thanks again for your time.
• 18:06
  We also want to thank our podcast sponsor,
• 18:07
  Eurek. You can tune in to more podcasts
• 18:09
  from Becker's Healthcare by visiting our podcast page
• 18:11
  at beckers hospital review
• 18:13
  dot com.