Latest / Becker’s Healthcare Podcast / The Role of AI in Transforming Medication Management and Pharmacy Leadership in Healthcare Systems

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The Role of AI in Transforming Medication Management and Pharmacy Leadership in Healthcare Systems · 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. So excited to
• 0:06
  - have you. Today, we're talking about the role
• 0:08
  - of AI in transforming medication management and pharmacy
• 0:11
  - leadership in health care systems.
• 0:13
  - And joining me for today's discussion, so excited
• 0:16
  - to have them both, is doctor Janjari Desai,
• 0:19
  - interim vice president pharmacy services at Stanford Health
• 0:22
  - Care, and doctor Seth Hartman, also vice president
• 0:25
  - clinical applications and chief pharmacy information officer at
• 0:29
  - UChicago
• 0:30
  - Medicine. Doctor Desai, doctor Hartman, so great to
• 0:32
  - have you on. Thanks for being here today.
• 0:34
  - Thank you so much for having us. Seth,
• 0:36
  - great to have you. We have a lot
• 0:37
  - to talk about. There is certainly a lot
• 0:39
  - of buzz still around the two lettered words
• 0:42
  - that we're going to discuss.
• 0:44
  - I wanna start us off with introduction. So,
• 0:46
  - doctor Desai, I'll start off with you. If
• 0:48
  - you could just introduce yourself and share a
• 0:50
  - little bit about your work in health care.
• 0:51
  - Sure. Thank again, thank you for having us
• 0:53
  - today. My name is Jandri Desai, and I'm
• 0:55
  - currently the interim VP of pharmacy services at
• 0:58
  - Stanford Health Care. I've been at Stanford for
• 1:00
  - a bit over a decade now in various
• 1:02
  - roles,
• 1:03
  - and I've had the pleasure of, you know,
• 1:06
  - working cross functionally across the organization with
• 1:10
  - various teams in that capacity.
• 1:12
  - And so I'm really excited to talk about
• 1:14
  - with Seth today,
• 1:16
  - the work that we're doing with AI in
• 1:18
  - the pharmacy space. Seth and I are both
• 1:21
  - also members of the Autonomous Pharmacy Advisory Board
• 1:25
  - and, have recently published a white paper,
• 1:28
  - that outlines a framework for the use of
• 1:30
  - AI for medication management. So hoping we can
• 1:33
  - dive into that a little bit as well.
• 1:34
  - Absolutely. Let's discuss. Doctor Hartman, over to you.
• 1:36
  - Yeah. Excellent. So as you said, my name
• 1:38
  - is Seth Hartman. I serve as the vice
• 1:39
  - president of, clinical applications
• 1:41
  - to set over the full, application portfolio for
• 1:44
  - all of our clinical workspaces at UChicago Medicine.
• 1:47
  - Then I also wear the head of chief
• 1:48
  - pharmacy information officer, pharmacist by training,
• 1:51
  - spent, you know, decades now working in pharmacy
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  - informatics and many different types of health systems
• 1:56
  - and,
• 1:57
  - different types of applications within those,
• 2:00
  - spheres. And so a lot of my work
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  - today is focused on, like, how do we
• 2:03
  - modernize our health systems, how do we make
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  - sure
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  - that we're really patient focused, and how do
• 2:08
  - we use the tools like AI and figure
• 2:09
  - out how to both evaluate and harness the
• 2:11
  - power of those and then guide ourselves forward
• 2:13
  - and the use of those to better patient
• 2:14
  - care. Yeah. And I mentioned,
• 2:17
  - up top of our episode here, everybody's talking
• 2:19
  - about it. Artificial intelligence is everywhere. AI is
• 2:22
  - everywhere, so to speak.
• 2:24
  - And it's part of a lot of workflows
• 2:28
  - right now, but it's also becoming, again, part
• 2:31
  - of pharmacy more than ever, across the board.
• 2:34
  - From your perspective,
• 2:36
  - where are you currently seeing the most opportunities
• 2:39
  - for AI to improve specifically medication management
• 2:43
  - across health systems? Doctor. Desai, I'll start off
• 2:45
  - with you.
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  - Sure. I think there's two components to consider.
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  - There's the administrative
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  - workflows, and then there are the clinical workflows.
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  - And I think a lot of the current
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  - innovation or the current,
• 2:57
  - AI vendors and platforms that are coming forward
• 2:59
  - are really focused on the former.
• 3:01
  - So when we think about, Ambient Scribes
• 3:05
  - or agentic
• 3:06
  - platforms that allow you to query the electronic
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  - health record,
• 3:10
  - platforms that automate the prior authorization
• 3:13
  - process or the prescription benefits check process,
• 3:16
  - those are really addressing administrative burdens and workflows
• 3:20
  - that exist today.
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  - You know, improving time to patient access, but
• 3:24
  - also
• 3:25
  - improving,
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  - I think, staff satisfaction. Right? Nobody wants to
• 3:28
  - go through these tedious, laborious
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  - workflows.
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  - And having an agent that you can work
• 3:33
  - with that helps you through that,
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  - makes the work just a little bit easier,
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  - I would say. And I think the opportunity
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  - really lies in that second bucket of, more
• 3:42
  - clinical support.
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  - And, rightfully so, I think,
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  - you know, everyone is approaching that with a
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  - little bit of caution,
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  - because of the direct potential impact on patient
• 3:53
  - care. But I still think that there are
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  - a lot of things that can be protocolized
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  - or that AI can pick up on maybe
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  - more quickly
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  - than we can pick up on. And so
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  - it's important that we figure out, you know,
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  - just as a health care community, what are
• 4:07
  - those use cases and then continue to iterate
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  - on that.
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  - Seth is doing a lot of work in
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  - the AI space as well. He's,
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  - doing some fantastic things at University of Chicago,
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  - so I'd love to hear his thoughts too.
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  - Yeah. Doctor Hartman, I I know governance is
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  - big pieces you've just mentioned, but I'd love
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  - to get your perspective on the opportunities
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  - that this presents as well. Absolutely. I think
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  - exactly as Chondry was kind of painting the
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  - picture of there, it's like, I I imagine
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  - we have this workforce, and we can do
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  - x number of things in a given day
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  - without AI. And then if we can start
• 4:35
  - embedding AI into the processes to smooth out
• 4:37
  - these workflows. Right? Automating PA so we spend
• 4:39
  - less time spending on the paper pushing and
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  - more time figuring out how does this medication
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  - impact that patient, and then we start figuring
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  - out how do how do we benefit ourselves
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  - in terms of, like, more advanced dosing algorithms
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  - and understanding the the population's needs around our
• 4:52
  - health system, and should we be investing in
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  - them in different ways and looking at things
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  - and spending more time in the social determinants
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  - of health and how that really impacts health
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  - care. Like, we can't do so many of
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  - those things today because of the administrative burden
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  - that kinda sits behind a lot of the
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  - tasks that we have to do in health
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  - care. And so as we use AI to
• 5:07
  - further our ability to automate those things that
• 5:10
  - can be automated and then support the end
• 5:12
  - clinician in terms of the decision making, the
• 5:14
  - research of the chart, and the other things
• 5:16
  - that need to be done to help them
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  - really figure out how to make the right
• 5:19
  - decisions for patient care. We allow ourselves to
• 5:21
  - move more quickly with the workforce that we
• 5:23
  - have. We're already looking at, you know, challenges
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  - with getting, you know, physicians into our health
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  - systems and getting pharmacists out through. We the
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  - enrollment is low in pharmacy schools and nursing
• 5:31
  - schools are the same, and so we're there's
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  - gonna be this really big problem in the
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  - next ten, fifteen years where as the baby
• 5:37
  - boomers are aging, more of them are needing
• 5:38
  - more health care and we are seeing lower
• 5:40
  - enrollments, we're gonna hit this nexus where if
• 5:42
  - we do not figure out how AI benefits
• 5:44
  - health care to make ourselves more efficient, we're
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  - gonna struggle to provide even basic care for
• 5:48
  - that population and their need. And so we
• 5:50
  - really have to lean into these technologies, but
• 5:52
  - lean into them safely
• 5:53
  - to make sure that we understand what they're
• 5:55
  - doing, why they're doing, how to train our
• 5:57
  - staff to use them, and how to make
• 5:58
  - sure that when we do use them, we're
• 5:59
  - doing them with the utmost benefit so that
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  - our humans can interact with the human patients
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  - on the other side and let a lot
• 6:04
  - of these documentation tasks and these other types
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  - of things fall back to the AI to
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  - automate those pieces so we can help these
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  - patients with what they actually need. Just to
• 6:14
  - illustrate this for our listeners, is there an
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  - initiative that you can point to specifically at
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  - your organization that illustrates this very well that
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  - shows that opportunity, that impact that you've just
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  - described?
• 6:24
  - Yeah. Actually, so we're we have a very
• 6:26
  - great opportunity at UChicago. We are building a
• 6:28
  - brand new cancer center. It goes live roughly
• 6:29
  - a year from today.
• 6:31
  - And this, cancer center, we're really focusing in
• 6:33
  - on the smart hospital room, and that's gonna
• 6:35
  - be laden with different technologies to make sure
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  - that we are delivering care to our patients
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  - in the best way. We have a vision
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  - that eventually, probably not an opening, but over
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  - years, we might be able to have these
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  - rooms be keyboard less. So we're in the
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  - room interacting with patients, having a human to
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  - human connection about their care, and the rest
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  - of that documentation that needs to happen in
• 6:53
  - that space is happening automatically.
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  - Now this takes a lot of work and
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  - effort and planning and figuring out how we
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  - engage our community in this and how we
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  - take all these next steps together. And so
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  - there's a lot of effort in figuring out
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  - AI today, a lot of governance work, a
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  - lot of time spent with our patient and
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  - family groups to figure out what their reactions
• 7:08
  - to these types of technologies are and how
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  - we bring them to them in a way
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  - that feels respectful to them and helps them
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  - understand that we're doing this for the betterment
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  - of their care. And that's the effort that's
• 7:17
  - being done across health systems today is figuring
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  - out how do we do this, how do
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  - we do it responsibly, ethically, and in the
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  - right ways to make sure that we can
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  - do these types of things in the future
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  - to make care that much better. Doctor Josiah,
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  - is there an initiative that sticks out for
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  - you?
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  - I would say that, you know, we're sort
• 7:34
  - of dabbling in a couple different initiatives.
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  - Both Seth and I have talked about the
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  - opportunities with prior authorization, and I think that's
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  - a space that most pharmacy organizations
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  - are already
• 7:44
  - either have adopted or on the path to
• 7:47
  - adopting. So I think that's an easy one
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  - just because, again, it is such a manual
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  - process. So anything is better than what the
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  - current state is.
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  - But the other things that we're dabbling in,
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  - at Stanford are using real world evidence also
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  - at the point of care.
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  - We have the benefit of having some homegrown
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  - real world evidence platforms that essentially will run
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  - analysis on our own data.
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  - And so we are able to
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  - essentially leverage that
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  - to either make interventions from a formulary perspective.
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  - Right? What what are we gonna add to
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  - formulary versus what may not actually be beneficial
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  - from both the efficacy safety, but also a
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  - cost perspective and really using that from a
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  - cost containment standpoint,
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  - but also using that to delineate
• 8:31
  - the clinical impact of our programs.
• 8:34
  - I think, you know, the whole role of
• 8:36
  - a pharmacist is to make sure things don't
• 8:39
  - happen.
• 8:40
  - So if you're doing that successfully, it's really
• 8:42
  - actually difficult
• 8:44
  - to quantify the impact of your role.
• 8:47
  - And, historically, it's been challenging to show the
• 8:50
  - impact of pharmacist intervention on either readmission rates
• 8:54
  - or, you know, specific clinical endpoints such as
• 8:58
  - a one c for diabetes.
• 9:00
  - But now with the power of AI and,
• 9:02
  - you know, having tools that essentially will comb
• 9:05
  - the chart in seconds and run these complex
• 9:07
  - analyses,
• 9:08
  - what we can actually show and demonstrate and
• 9:10
  - we have at Stanford
• 9:12
  - is that when a pharmacist is involved in
• 9:14
  - the patient's care, we're able to help them
• 9:16
  - achieve their, a one c goal for their
• 9:19
  - diabetes more quickly.
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  - And and those patients are actually more likely
• 9:23
  - to achieve their goal than if, compared to
• 9:26
  - standard of care. And so I think that's
• 9:28
  - really exciting,
• 9:30
  - you know, not just from a clerical standpoint
• 9:32
  - or administrative standpoint to use AI in those
• 9:35
  - ways, but really to use
• 9:37
  - AI to identify where are the opportunities for
• 9:40
  - us
• 9:41
  - to augment or maybe even change our workflow
• 9:44
  - so that we're delivering
• 9:45
  - true value focused, value based care to our
• 9:49
  - patients.
• 9:50
  - Speaking of of providing that value,
• 9:52
  - to be able to do that,
• 9:54
  - you have to be aligned around these initiatives.
• 9:56
  - People have to be working together. Otherwise,
• 9:58
  - there's very isolated impact. Right? What does it
• 10:01
  - take to create that alignment across organizations
• 10:03
  - for you? And
• 10:05
  - are there any examples where you think we
• 10:07
  - aligned
• 10:08
  - and have really worked? Are there certain outcomes
• 10:11
  - that stick out to you because of that
• 10:13
  - alignment?
• 10:14
  - Yes. Maybe just using that same example. It's
• 10:17
  - a little bit of chicken and the egg.
• 10:19
  - You gotta start somewhere. Right? And so, initially,
• 10:21
  - maybe there wasn't that shared understanding or that
• 10:24
  - shared alignment on the value that the pharmacist
• 10:27
  - brings in primary care.
• 10:29
  - But once we had the data to show
• 10:32
  - and to demonstrate that as we continue to
• 10:35
  - socialize that, now, you know, the conversation is
• 10:38
  - more around, okay.
• 10:40
  - Where else can we leverage pharmacists in the
• 10:42
  - care? Right? Thinking about the care model at
• 10:45
  - large, when does it make sense for a
• 10:47
  - pharmacist to be involved? And so those conversations
• 10:49
  - aren't just happening, you know, with myself or
• 10:52
  - other pharmacy leaders. They're happening with our service
• 10:54
  - line leaders to say, you know, hey. That
• 10:57
  - team benefited from pharmacist involvement. How can we
• 11:01
  - have some of that too? And rather than
• 11:03
  - having siloed conversations with each service line, it's
• 11:06
  - more globally. Okay. Let's define the role of
• 11:08
  - the pharmacist in the organization or in ambulatory
• 11:11
  - care specifically.
• 11:13
  - Doctor Hartman, just to come back to your
• 11:14
  - example that you mentioned in terms of building
• 11:15
  - a a new building. Right? That certainly needs
• 11:18
  - alignment.
• 11:19
  - People have differing opinions about what works. But
• 11:21
  - what does this look like for you? Are
• 11:22
  - there specific examples that you can point to
• 11:24
  - where you think, okay. We aligned. We talked
• 11:27
  - about it. What does it take? Right? But
• 11:29
  - it actually worked because we were aligned, and
• 11:31
  - we had conversations about this. Yeah. Absolutely. And
• 11:34
  - I think
• 11:35
  - the the cancer center example that we had
• 11:37
  - is a great platform for looking at this
• 11:39
  - because we're trying to do truly innovative things
• 11:42
  - in the space, but it also means that
• 11:44
  - the folks that are providing care in the
• 11:45
  - space, the patients that will be in the
• 11:47
  - space, the providers that will, like, exist in
• 11:49
  - that space as well, have to be on
• 11:50
  - board with what it is you wanna do.
• 11:52
  - There are myriad different takes on different AI
• 11:54
  - technologies, whether that's computer vision and having cameras
• 11:54
  - at the bedside or whether that's, technologies, whether
• 11:55
  - that's computer vision and having cameras at the
• 11:57
  - bedside or whether that's,
• 11:59
  - ambient recording for audio devices. And you're gonna
• 12:01
  - have people who are very pro and want
• 12:03
  - to do this today, and you're gonna have
• 12:04
  - people who are very resistant and don't ever
• 12:07
  - want to have this in the space. And
• 12:08
  - so you have to bring all those groups
• 12:10
  - together. You have to discuss the true risks,
• 12:11
  - the true benefits, really look at the ROI
• 12:13
  - on these different things. So that ROI is
• 12:15
  - greater than what are the revenues associated with
• 12:17
  - it, but what is the betterment to the
• 12:18
  - patient? What is the betterment to the providers
• 12:21
  - who are providing this care? And how can
• 12:22
  - we make this easier for everyone? And then
• 12:25
  - make difficult decisions
• 12:26
  - on should we or shouldn't we. And walking
• 12:27
  - down those paths is difficult, and it takes,
• 12:29
  - you know, many different perspectives in a room
• 12:31
  - and a lot of conversations. And we're truly
• 12:33
  - in the middle of this process right now.
• 12:35
  - You know, my my team on the IT
• 12:37
  - side is building the system while we're working
• 12:38
  - with a group who's stitching together new operational
• 12:41
  - workflows. And every week, we're having cross pollinating
• 12:43
  - meetings where those ideas are being shared. We're
• 12:45
  - finding new issues, having new discussions, making new
• 12:47
  - decisions around things, and we're coming back all
• 12:49
  - trained to land this at the beginning of
• 12:51
  - the summer so that we can then start
• 12:52
  - testing and vetting and training until we can
• 12:54
  - open this thing in a year from now.
• 12:56
  - And so these these conversations are happening dynamically,
• 12:59
  - and a lot of those decisions are made
• 13:00
  - as a result of getting all of the
• 13:02
  - right voices in the room and making sure
• 13:03
  - you're not missing an important component of that.
• 13:05
  - Can I actually add Yeah? Go ahead. Comment
• 13:07
  - to that. As Seth was talking, I also
• 13:09
  - was thinking about this from just a economics
• 13:11
  - perspective. Yeah. I think that,
• 13:14
  - that cross pollination or that collaboration is actually
• 13:17
  - necessary if you're gonna adapt adopt these technologies.
• 13:20
  - Otherwise, I'm not sure that the ROI would
• 13:23
  - pan out. Mhmm. So something else that we're
• 13:25
  - exploring today
• 13:27
  - is the use of, you know, robotic delivery
• 13:30
  - systems.
• 13:31
  - And if I look at that and just
• 13:32
  - take pharmacy or medications as the use case,
• 13:36
  - the cost of these technologies
• 13:37
  - is usually, you know, pretty significant.
• 13:40
  - And so I don't know, you know, it's
• 13:42
  - really a comparison of the robot versus labor,
• 13:45
  - which one would win out.
• 13:47
  - And I don't know, especially in the Bay
• 13:49
  - Area, which one would actually what I was
• 13:51
  - gonna say.
• 13:53
  - So but then I have to think more
• 13:55
  - broadly. It's not just you know, pharmacy is
• 13:58
  - not the only group that needs these these
• 14:00
  - types of technologies. Who are my other key
• 14:02
  - stakeholders? So partnering with our lab colleagues, our
• 14:05
  - nursing colleagues,
• 14:06
  - food services, etcetera, who all are delivering things
• 14:09
  - across the organization.
• 14:11
  - So how do we all come together and
• 14:13
  - identify
• 14:14
  - one vendor who can actually
• 14:17
  - support all of those needs? And then with
• 14:19
  - that scale,
• 14:21
  - not only does it make the economics panel,
• 14:23
  - but it also gives us greater bargaining power.
• 14:25
  - Yeah. Absolutely. You mentioned something really important here,
• 14:29
  - sort of the the overarching trend. This is
• 14:31
  - developing so fast. There's new things every single
• 14:34
  - time.
• 14:36
  - As we close our conversation,
• 14:38
  - how is this going to reshape
• 14:40
  - pharmacists,
• 14:41
  - pharmacy leaders, etcetera? How is it going to
• 14:43
  - impact them? How is AI going to impact
• 14:45
  - them?
• 14:46
  - And, again,
• 14:47
  - what capabilities will pharmacy teams need to develop
• 14:51
  - to be able to keep up and operationalize
• 14:53
  - this at scale?
• 14:54
  - I'll start off with you.
• 14:56
  - Yeah. There there's a whole host of changes
• 14:59
  - that I think will come come from this.
• 15:00
  - Some of them in the short term, some
• 15:01
  - in the long term. Mhmm. I think in
• 15:03
  - the short term, upskilling staff to understand how
• 15:05
  - to react to, use, respond to these models,
• 15:09
  - understand what it means to have drift, how
• 15:11
  - to assess for drift.
• 15:13
  - I think it creates some new roles in
• 15:14
  - the workforce in terms of you you you
• 15:16
  - know, today, we have, like, a data science
• 15:18
  - team who does a their work is really
• 15:20
  - focused on these models. If you have, you
• 15:22
  - know, hundreds of these models deployed across every
• 15:24
  - department in your health system, pharmacy is gonna
• 15:26
  - need their own data scientists who are skilled
• 15:28
  - in understanding pharmacist workflows,
• 15:30
  - clinical decision that's made in that space, and
• 15:32
  - how to assess for drift in a population
• 15:34
  - that, you know, one or two percent of
• 15:35
  - drift might have a meaningful impact across those.
• 15:38
  - You're also gonna need to make sure that
• 15:40
  - you are looking long term at what these
• 15:42
  - mean. You know? So AI is really good
• 15:44
  - at understanding what's happening, creating information flow, and
• 15:47
  - trying to do things in terms of, like,
• 15:48
  - summarization and bringing things together. This probably means
• 15:52
  - a a broadening of what needs to be
• 15:53
  - done of, like, putting supervisors closer to the
• 15:55
  - front lines and putting senior leaders a little
• 15:57
  - bit higher because that middle gap that's happening
• 15:59
  - there, that information flow that a lot of
• 16:01
  - that management layer is doing today can be
• 16:04
  - tackled by these individuals, which means you need
• 16:07
  - more people looking at these agents, which is
• 16:09
  - probably an elevation of some roles, and then
• 16:11
  - you need some more people closer to the
• 16:13
  - front lines serving as those experts for how
• 16:15
  - to use these tools effectively and to how
• 16:17
  - to manage that work. And so I think
• 16:18
  - we're really gonna see the workplace shift dynamically,
• 16:22
  - and we're gonna see that there is a
• 16:24
  - lot more capability
• 16:25
  - that's handed to the humans that are interacting
• 16:27
  - with patients. The agents that are interacting with
• 16:30
  - patients will be taking on a lot more
• 16:31
  - tasks. So, hopefully, it feels like the human
• 16:33
  - touch of care is a lot more realized
• 16:35
  - in that future state so that as a
• 16:38
  - pharmacist, as a pharmacy technician, even you have
• 16:40
  - more time at that patient's bedside than you
• 16:43
  - do behind the computer dealing with all the
• 16:45
  - documentation and approvals and all the things that
• 16:47
  - we do today. It comes back to patient
• 16:49
  - outcomes and and better care for the patient,
• 16:50
  - which is so crucial. Yeah. Doctor Desai, same
• 16:52
  - question for you. How is this going to
• 16:54
  - reshape pharmacy?
• 16:55
  - Yeah. I'm smiling because this is something Seth
• 16:57
  - and I have actually discussed at length. So
• 16:59
  - I'm just gonna ditto and think Absolutely. Discuss
• 17:02
  - that.
• 17:03
  - But I think there's also an opportunity for
• 17:05
  - us to really think proactively about
• 17:08
  - what does the pharmacy technician of the future
• 17:11
  - look like and what does the pharmacist of
• 17:13
  - the future look like. There's, you know, these,
• 17:16
  - core competencies
• 17:17
  - or core tasks that we all,
• 17:20
  - perform today. Those aren't going away,
• 17:23
  - but the question is who is performing those
• 17:25
  - in the future and how are they performing
• 17:28
  - it. And so I think, you know, historically,
• 17:30
  - our pharmacy technicians have been very tied to
• 17:32
  - the drug and have been the ones preparing
• 17:35
  - the doses,
• 17:36
  - compounding the doses, etcetera.
• 17:38
  - Now with increasing automation,
• 17:40
  - maybe they're not maybe the pharmacy technician of
• 17:42
  - the future is more trained
• 17:44
  - from a technical standpoint or a data science
• 17:48
  - standpoint to really understand
• 17:50
  - and optimize the technologies that we're using. And
• 17:53
  - then to Seth's point, the pharmacist of the
• 17:55
  - future,
• 17:56
  - this is something, you know, I think we
• 17:58
  - as a profession have been waiting for for
• 18:00
  - so long, just being recognized as clinicians, as
• 18:03
  - providers, and actually focusing on providing that direct
• 18:07
  - patient care rather than being more behind the
• 18:10
  - scenes all of the time,
• 18:11
  - verifying orders and and doing other things more
• 18:14
  - tied to the dispensation of a medication.
• 18:17
  - And all of this is I I think
• 18:18
  - it's wonderful because to set point earlier about,
• 18:21
  - workforce shortages, it's coming.
• 18:24
  - And so how can we really spread our
• 18:26
  - precious resources to ensure
• 18:28
  - fantastic, safe, and effective care for our patients?
• 18:31
  - It's so great to have you both on.
• 18:33
  - Thanks so much for being here. Thank you.
• 18:35
  - So much. It's great to have you. And
• 18:36
  - we also want to thank our podcast sponsor,
• 18:38
  - Omnicell. You can tune into more podcasts from
• 18:40
  - Becker's Healthcare by visiting our podcast page at
• 18:42
  - beckershospitalreview.com.