- This is Laura Dedo with the Becker's Healthcare Podcast.
I'm thrilled today to be joined by Dr. Alan Weiss,
vice President and Chief Medical Information Officer at
BayCare Health System, Dr. Weiss, it's a pleasure
to have you on the podcast today.
- Thanks for having me.
- Now, I know we have a lot to talk about.
There's so much happening and changing in healthcare,
and certainly I'm excited to learn more about
what you're planning for BayCare in the next year.
But before we dive into those questions,
can you tell me a little bit more
about yourself and your background?
- Sure. So I have a, sort
of a different background than a lot
of people in my position.
I, I actually have a computer science undergraduate degree.
It's actually computer science
and philosophy from, uh, the University of Michigan.
And went
and did work in the pharmaceutical, uh, industry,
basically helping to create databases for drug approvals
and analyze those databases for the FDA
and for medical journals.
And after I worked there for several years, I turned around
and got an MBA with a focus both in healthcare management
and the management of information systems.
And finally, um, got so interested in medicine
through working in the pharmaceutical industry
that I decided to, to take the plunge.
I became a, went to medical school, did my, uh,
residency in internal medicine at the Johns Hopkins Bayview
Medical Center, and returned to, um, Cleveland, Ohio,
which is where I'm from, to work at the Cleveland Clinic
for about 10 years.
I was a practicing physician there,
but I also helped out with informatics.
I had, uh, worked in business informatics.
I had a, a number of different positions in addition to
seeing patients, I was also teaching both medical students
and residents and, uh, doing a, and,
and I was the ward attending as well.
So a lot of
different things that I did at the Cleveland Clinic.
It was a lot of fun and, and certainly a, a growth career.
I, I ended up moving from, uh, the Cleveland Clinic
to Los Angeles where I was the, uh, the physician in charge
of their epic rollout on the inpatient side.
And I, that goes back a ways,
but spent several years there helping them develop their
epic implementation before moving on to Memorial Hermann at,
uh, or in Houston, Texas, which is where my wife is from.
And we spent about five years there
as their ambulatory Chief Medical Information Officer
working on a variety of different EHRs,
including GE centricity, uh, eClinical works,
and, uh, also Cerner while I was there.
And I had a very interesting time there.
It was very interesting, tried to figure out
how we could encode, uh, quality into the, the EHR and,
and also help out with efficiency issues.
Uh, I, five years ago, I, I moved here to Tampa, Florida,
which is, uh, you know, where I'm, where I'm located now.
I, I'm the, the Chief Medical Information Officer
for the BayCare Health System here.
And, uh, BayCare is the largest
healthcare provider in Tampa.
And we, um, uh, we like to say the qualities are true north,
and, uh, that's essentially my background.
- Well, that's fantastic to hear
and what amazing experiences you've had throughout your
career, whether your early career, um, you know,
in computer science, in, in doing, um,
several different aspects of healthcare
and then jumping into, um, you know, practicing medicine
and being in so many different places.
And, and then too, um, heading up on the medical side,
an EHR rollout.
I can imagine you've just seen so many things, um, coming
through the system and now looking ahead, you know,
a completely different healthcare system, um, is evolving.
So I'm excited to hear about that.
- Absolutely. It's, it's, it's been
a really amazing experience.
I, I've, and, uh, you know,
sometimes I could say it hasn't been as much fun
as it sounds, but it, it's been certainly a,
a very interesting learning experience as,
as I've gone from different healthcare systems
and had different varieties of, uh, projects
and experiences throughout the course of my career.
- Absolutely. Well, you know, now looking ahead,
what are some of the biggest issues that you're following,
taking you into the next 12 months?
Um, what's kind of top of mind for you?
- Well, what's always top of mind for me
is the electronic health record
and how we can try to make it better than
what it currently is.
I mean, it's, it's always an optimization adventure for us.
And, and for us, it comes down to how,
how can we collect the data
that's more clinically appropriate, more, more clinically
accurate, and serve it up to the physicians in a way
that allows them to make better healthcare decisions.
It also involves figuring out how we can help our, our, uh,
entire team write documents in an easier way, organize them
so you can find them easier.
And, and the, the same with orders.
Um, you know, how, how do you make it easier for, for people
to find the orders that are needed
and then display the orders in a concise, um,
consistent manner so that people can carry them out in,
in a way that makes sense.
Part of those optimization efforts also involve ways
of trying to embed evidence-based medicine,
into the work that people are doing.
And, uh, also to help us.
And as like, like other healthcare systems, we're trying
to do a care transformation project where
we both reduced the cost of healthcare
and improved the efficiency.
So a lot of different projects out there, A lot of, uh,
interesting projects on the EHR front in, in addition to
that, I, I tell you, we certainly are working very
diligently on, uh, a number of AI initiatives,
and I can give more details on that later on.
Um, trying to, to figure out how we, we,
like many other healthcare systems, uh, are, are trying to,
to, uh, uh, you know, address what is now a,
a very transformative type of technology in healthcare.
Um, I would finally say that that certainly part
of our efficiency issues, part
of our EHR issues involve our nurses.
We are very deeply involved with trying to figure out
how we make nurses more efficient,
and, uh, once again, it's, it's all about trying
to figure out how to display information
for our nurses in a better way, cut down on the tasks
that they have and improve the work that they do.
I mean, so it's a lot of, a lot of effort all throughout.
- That's amazing to hear, and certainly so important,
as you said, in looking at the current environment,
making sure that, you know,
you're leveraging technology in the EHR
to optimize everything you can, um,
to support the workforce in,
in operational efficiency while also cutting costs
where it makes sense and being more efficient
and effective in that way.
And, and I appreciate you sharing all these examples
because I think it's certainly, um, you know,
so many different projects can come across your desk,
and yet they all kind of seem
to dovetail into having the same mission or,
or driving forward the, a similar strategy
and mission throughout the health system.
- Exactly, exactly.
- So, um, given everything we just talked about,
what are some of the things you're most excited about right
now and what makes you nervous?
- True. Um, I, I'm, I'm very excited, um,
about the promise of ai.
I, I, I think there's just so much that you could be doing
with AI right now.
I, I, I, I'm, I'm very excited by, uh,
by its potential and possibility.
Um, we are in the process of doing some
of the ambient listening, uh, pilots right now and,
and trying to figure out how we're gonna approach this.
Uh, we're having lots of discussions about
how you use generative AI in medicine.
Those are just a couple of of things that, that excite me
and make me very interested.
I mean, I, it's fascinating to me.
Um, I get, uh, very excited just by the efficiency of
what we can do with the EHR.
One of the things that we're doing is,
another example is we're automating tasks using the EHR.
So we are literally taking millions of things
that physicians and their staff would be doing,
and we are instead, um, pushing that into the EHR
and letting it be done automatically.
That's improving reimbursement,
it's improving quality, it's improving safety.
So we're very excited about that kind of work.
It's really, it's, it's fantastic.
Um, so I'm, I'm very, very excited by all of these things.
The things that that scare me.
Um, I get a little scared by AI
and I, I'm probably not the only one.
There's, there's all kinds of biases that AI has been known
to have, and,
and I I would tell you that, that one of the things
that we are finding is that, uh, some of the AI
companies out there that say that they're doing AI
are probably not doing AI as much as they're doing, um,
some advanced logic, you know, AI by itself of a, a system
that learns on its own is, uh, well, we're,
we're just finding that a lot of, uh, the companies
that are saying they're doing AI really aren't,
and we're not having universal success in the ai We're
finding that there's a lot of, of times when the, um,
the, the AI isn't quite performing as
to the metrics that we've created.
So I, I'm, I'm worried about those, those kinds of,
of efforts that, that are out there.
I, I think they're certainly worth pursuing,
but they're worth pursuing with the same kind of diligence
that we should have or any kind of healthcare system
or any kind of application.
Uh, making sure that we understand the implications
of the system before we get into 'em, and,
and that we make sure that we we're, we're, uh,
approaching them with the, the, the right due diligence
by our is, uh, colleagues.
So I, I, what scares me is, is in some ways
what also excites me.
- Yeah, that's such a great point.
And certainly looking at artificial intelligence,
it's such in early stages right now,
especially within the healthcare spaces and,
and applications that could really make a big difference
both clinically and operationally from your perspective.
I, I know you talked a little bit about, um, some
of the challenges, whether it's the biases
and then, you know, jumping into, um,
the AI not exactly doing, um, what was anticipated
or having the results that were anticipated.
How do you, uh, really work with your team on that, um,
you know, who maybe don't necessarily understand the
technology, but are skeptical
and are seeing some of these challenges as validating that
and, and thinking that, you know, potentially, um, having,
creating more questions than answers amongst team members.
Um, is that something you're seeing
or have people been pretty quick to embrace the change
and understanding of the process on, you know,
incorporating new technology into the healthcare space?
- Yeah, the, the, the problem is,
and I think this, this is a
a a probably a fundamental aspect of the excitement
that we get about new technology is that the,
the new technology is so fascinating.
It's so interesting. And you, you read the examples of
what AI can do and let's face it chat.
GPT is, it's, it's cool.
There's a lot of just really interesting things
that generative AI can do, and it,
and it, it certainly has captured our imaginations.
And, you know,
when we start thinking about the administrative overhead
that is so, uh, problemsome for people
inside of medicine, the, the opportunities to have an AI
to help address the issues is just amazing.
So I, I, I think there's, there's lots of great excitement.
The the problem is that there's also a lack of understanding
and that lack of understanding and knowledge is one
of the things we face on regular basis.
For instance, I mean, I, I tell you, when you start to look
at, at ai, you know, we, we have, we have, um, execs
and we have users who come up to me
and say, well, we need AI to solve, you know, to help us.
And I, I guess the, the issue that always comes up is
what we, we need to do is, is to understand what the nature
of the problem is around whatever issue there is that they,
they they want AI for, and then decide whether
or not AI is the right approach to help address the issue.
I mean, AI is a tool like many other tools that we have.
I tell you that most of the AI
that we've looked at is a very expensive tool,
and that expense, you know, can, can help inhibit the notion
of it being adopted or, um, by our organization.
I think we have to be very careful.
Um, when I start to talk to users about all of the issues
that are out there, there's, um, there's almost a hesitancy
for me to actually make those kinds of statements.
You know, there's so many people that just want
to plow ahead without thinking about the, uh, the dangers
and the issues that are out there.
I think we, we have to approach AI with caution,
with some notion that we have to, you know, make sure
that it's proven and we have to make sure
that there are very defined metrics for its use
before we, uh, before and, and as we adopt.
- That's such a great point.
Thank you so much for sharing just your thought process
there, and especially how other clinicians are,
are viewing AI and, and technology integration in general.
Now, I know we've talked about a lot
of different changes within the healthcare space
and how it's evolving so rapidly.
What do you think is going
to be the most effective thing healthcares will need
to be successful over the next two to three years?
What should leaders do and understand,
and what will they need to do, um, to make sure
that their organizations are successful?
- So, I, I would tell you that, that when I start to talk
to my colleagues, uh, around the, the, uh,
the country, a lot
of them are facing the same kind of things that we're facing.
There's, um, uh, revenue challenges,
and I, I think a lot of healthcare organizations
have since, uh, since Covid, they, they've,
they've really had to, um, rethink of
how they can reduce costs, improve quality,
and do so in a way that, uh, can, can somehow promise all
of this at a lower cost.
I think that those, those issues are paramount to a lot
of the organizations and,
and a lot of people, uh, I,
I do think there's gonna be a continual, uh, focus on
how do we improve the quality of the work that we provide.
Uh, I'm just seeing that more
and more often as, as I talk to people,
those quality initiatives are becoming, well,
it's not like they weren't, you know, prevalent beforehand,
but they're, they're becoming even more important
and the use of the EHR
and other clinical tools to help in the process
of delivering care, it's becoming more
and more, um, you know, more
and more of a project, more of a learning issue.
So I, I think that's something that, that you'll see more
of as time goes on.
Um, I would also say,
and when I, I, I start to, to think about the, um,
the issues and projects that people start to, to work on, I,
I do think that we are going to see more
and more integration across the healthcare system
and the healthcare environment that, that integration,
what I mean by that is, is more ways of integrating data
and operations, uh, about patients
and making it into a more
wholesome approach to patient care.
I think we're gonna find that the data that patients have
and collect on their everyday lives are gonna start
to impact the way that we treat patients.
Uh, I think you're gonna see more wearables in the system.
I think you're gonna see patients have reported outcomes
will start to drive the, the way we, we, uh, handle care.
So I, I think that's all there.
Um, I, I would also tell you that digital transformation
continues to be an issue that we start to work on so
that a lot of different facilities
that we have within the healthcare system,
I think are gonna be, be produced
or will be evaluated in such a way that, uh, they'll,
they'll move to digital tools.
- That's fascinating to hear.
Dr. Weiss, thank you so much
for joining us on the podcast today.
This has been such a fun and fascinating conversation,
and I look forward to connecting with you again soon.
- Sounds good. Thank you very much.
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