Latest / Becker’s Healthcare - Clinical Leadership Podcast / Alan Weiss, Chief Medical Information Officer at BayCare Health System

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Alan Weiss, Chief Medical Information Officer at BayCare Health System · Becker’s Healthcare - Clinical Leadership Podcast

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  - This is Laura Dedo with the Becker's Healthcare Podcast.
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  I'm thrilled today to be joined by Dr. Alan Weiss,
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  vice President and Chief Medical Information Officer at
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  BayCare Health System, Dr. Weiss, it's a pleasure
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  to have you on the podcast today.
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  - Thanks for having me.
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  - Now, I know we have a lot to talk about.
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  There's so much happening and changing in healthcare,
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  and certainly I'm excited to learn more about
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  what you're planning for BayCare in the next year.
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  But before we dive into those questions,
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  can you tell me a little bit more
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  about yourself and your background?
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  - Sure. So I have a, sort
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  of a different background than a lot
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  of people in my position.
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  I, I actually have a computer science undergraduate degree.
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  It's actually computer science
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  and philosophy from, uh, the University of Michigan.
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  And went
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  and did work in the pharmaceutical, uh, industry,
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  basically helping to create databases for drug approvals
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  and analyze those databases for the FDA
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  and for medical journals.
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  And after I worked there for several years, I turned around
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  and got an MBA with a focus both in healthcare management
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  and the management of information systems.
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  And finally, um, got so interested in medicine
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  through working in the pharmaceutical industry
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  that I decided to, to take the plunge.
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  I became a, went to medical school, did my, uh,
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  residency in internal medicine at the Johns Hopkins Bayview
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  Medical Center, and returned to, um, Cleveland, Ohio,
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  which is where I'm from, to work at the Cleveland Clinic
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  for about 10 years.
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  I was a practicing physician there,
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  but I also helped out with informatics.
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  I had, uh, worked in business informatics.
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  I had a, a number of different positions in addition to
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  seeing patients, I was also teaching both medical students
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  and residents and, uh, doing a, and,
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  and I was the ward attending as well.
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  So a lot of
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  different things that I did at the Cleveland Clinic.
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  It was a lot of fun and, and certainly a, a growth career.
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  I, I ended up moving from, uh, the Cleveland Clinic
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  to Los Angeles where I was the, uh, the physician in charge
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  of their epic rollout on the inpatient side.
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  And I, that goes back a ways,
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  but spent several years there helping them develop their
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  epic implementation before moving on to Memorial Hermann at,
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  uh, or in Houston, Texas, which is where my wife is from.
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  And we spent about five years there
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  as their ambulatory Chief Medical Information Officer
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  working on a variety of different EHRs,
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  including GE centricity, uh, eClinical works,
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  and, uh, also Cerner while I was there.
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  And I had a very interesting time there.
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  It was very interesting, tried to figure out
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  how we could encode, uh, quality into the, the EHR and,
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  and also help out with efficiency issues.
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  Uh, I, five years ago, I, I moved here to Tampa, Florida,
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  which is, uh, you know, where I'm, where I'm located now.
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  I, I'm the, the Chief Medical Information Officer
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  for the BayCare Health System here.
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  And, uh, BayCare is the largest
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  healthcare provider in Tampa.
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  And we, um, uh, we like to say the qualities are true north,
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  and, uh, that's essentially my background.
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  - Well, that's fantastic to hear
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  and what amazing experiences you've had throughout your
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  career, whether your early career, um, you know,
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  in computer science, in, in doing, um,
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  several different aspects of healthcare
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  and then jumping into, um, you know, practicing medicine
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  and being in so many different places.
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  And, and then too, um, heading up on the medical side,
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  an EHR rollout.
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  I can imagine you've just seen so many things, um, coming
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  through the system and now looking ahead, you know,
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  a completely different healthcare system, um, is evolving.
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  So I'm excited to hear about that.
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  - Absolutely. It's, it's, it's been
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  a really amazing experience.
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  I, I've, and, uh, you know,
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  sometimes I could say it hasn't been as much fun
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  as it sounds, but it, it's been certainly a,
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  a very interesting learning experience as,
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  as I've gone from different healthcare systems
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  and had different varieties of, uh, projects
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  and experiences throughout the course of my career.
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  - Absolutely. Well, you know, now looking ahead,
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  what are some of the biggest issues that you're following,
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  taking you into the next 12 months?
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  Um, what's kind of top of mind for you?
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  - Well, what's always top of mind for me
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  is the electronic health record
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  and how we can try to make it better than
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  what it currently is.
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  I mean, it's, it's always an optimization adventure for us.
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  And, and for us, it comes down to how,
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  how can we collect the data
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  that's more clinically appropriate, more, more clinically
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  accurate, and serve it up to the physicians in a way
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  that allows them to make better healthcare decisions.
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  It also involves figuring out how we can help our, our, uh,
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  entire team write documents in an easier way, organize them
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  so you can find them easier.
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  And, and the, the same with orders.
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  Um, you know, how, how do you make it easier for, for people
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  to find the orders that are needed
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  and then display the orders in a concise, um,
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  consistent manner so that people can carry them out in,
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  in a way that makes sense.
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  Part of those optimization efforts also involve ways
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  of trying to embed evidence-based medicine,
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  into the work that people are doing.
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  And, uh, also to help us.
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  And as like, like other healthcare systems, we're trying
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  to do a care transformation project where
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  we both reduced the cost of healthcare
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  and improved the efficiency.
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  So a lot of different projects out there, A lot of, uh,
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  interesting projects on the EHR front in, in addition to
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  that, I, I tell you, we certainly are working very
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  diligently on, uh, a number of AI initiatives,
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  and I can give more details on that later on.
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  Um, trying to, to figure out how we, we,
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  like many other healthcare systems, uh, are, are trying to,
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  to, uh, uh, you know, address what is now a,
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  a very transformative type of technology in healthcare.
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  Um, I would finally say that that certainly part
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  of our efficiency issues, part
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  of our EHR issues involve our nurses.
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  We are very deeply involved with trying to figure out
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  how we make nurses more efficient,
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  and, uh, once again, it's, it's all about trying
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  to figure out how to display information
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  for our nurses in a better way, cut down on the tasks
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  that they have and improve the work that they do.
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  I mean, so it's a lot of, a lot of effort all throughout.
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  - That's amazing to hear, and certainly so important,
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  as you said, in looking at the current environment,
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  making sure that, you know,
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  you're leveraging technology in the EHR
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  to optimize everything you can, um,
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  to support the workforce in,
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  in operational efficiency while also cutting costs
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  where it makes sense and being more efficient
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  and effective in that way.
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  And, and I appreciate you sharing all these examples
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  because I think it's certainly, um, you know,
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  so many different projects can come across your desk,
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  and yet they all kind of seem
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  to dovetail into having the same mission or,
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  or driving forward the, a similar strategy
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  and mission throughout the health system.
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  - Exactly, exactly.
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  - So, um, given everything we just talked about,
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  what are some of the things you're most excited about right
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  now and what makes you nervous?
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  - True. Um, I, I'm, I'm very excited, um,
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  about the promise of ai.
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  I, I, I think there's just so much that you could be doing
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  with AI right now.
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  I, I, I, I'm, I'm very excited by, uh,
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  by its potential and possibility.
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  Um, we are in the process of doing some
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  of the ambient listening, uh, pilots right now and,
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  and trying to figure out how we're gonna approach this.
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  Uh, we're having lots of discussions about
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  how you use generative AI in medicine.
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  Those are just a couple of of things that, that excite me
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  and make me very interested.
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  I mean, I, it's fascinating to me.
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  Um, I get, uh, very excited just by the efficiency of
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  what we can do with the EHR.
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  One of the things that we're doing is,
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  another example is we're automating tasks using the EHR.
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  So we are literally taking millions of things
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  that physicians and their staff would be doing,
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  and we are instead, um, pushing that into the EHR
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  and letting it be done automatically.
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  That's improving reimbursement,
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  it's improving quality, it's improving safety.
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  So we're very excited about that kind of work.
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  It's really, it's, it's fantastic.
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  Um, so I'm, I'm very, very excited by all of these things.
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  The things that that scare me.
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  Um, I get a little scared by AI
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  and I, I'm probably not the only one.
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  There's, there's all kinds of biases that AI has been known
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  to have, and,
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  and I I would tell you that, that one of the things
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  that we are finding is that, uh, some of the AI
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  companies out there that say that they're doing AI
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  are probably not doing AI as much as they're doing, um,
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  some advanced logic, you know, AI by itself of a, a system
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  that learns on its own is, uh, well, we're,
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  we're just finding that a lot of, uh, the companies
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  that are saying they're doing AI really aren't,
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  and we're not having universal success in the ai We're
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  finding that there's a lot of, of times when the, um,
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  the, the AI isn't quite performing as
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  to the metrics that we've created.
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  So I, I'm, I'm worried about those, those kinds of,
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  of efforts that, that are out there.
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  I, I think they're certainly worth pursuing,
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  but they're worth pursuing with the same kind of diligence
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  that we should have or any kind of healthcare system
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  or any kind of application.
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  Uh, making sure that we understand the implications
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  of the system before we get into 'em, and,
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  and that we make sure that we we're, we're, uh,
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  approaching them with the, the, the right due diligence
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  by our is, uh, colleagues.
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  So I, I, what scares me is, is in some ways
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  what also excites me.
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  - Yeah, that's such a great point.
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  And certainly looking at artificial intelligence,
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  it's such in early stages right now,
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  especially within the healthcare spaces and,
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  and applications that could really make a big difference
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  both clinically and operationally from your perspective.
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  I, I know you talked a little bit about, um, some
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  of the challenges, whether it's the biases
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  and then, you know, jumping into, um,
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  the AI not exactly doing, um, what was anticipated
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  or having the results that were anticipated.
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  How do you, uh, really work with your team on that, um,
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  you know, who maybe don't necessarily understand the
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  technology, but are skeptical
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  and are seeing some of these challenges as validating that
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  and, and thinking that, you know, potentially, um, having,
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  creating more questions than answers amongst team members.
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  Um, is that something you're seeing
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  or have people been pretty quick to embrace the change
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  and understanding of the process on, you know,
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  incorporating new technology into the healthcare space?
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  - Yeah, the, the, the problem is,
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  and I think this, this is a
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  a a probably a fundamental aspect of the excitement
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  that we get about new technology is that the,
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  the new technology is so fascinating.
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  It's so interesting. And you, you read the examples of
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  what AI can do and let's face it chat.
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  GPT is, it's, it's cool.
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  There's a lot of just really interesting things
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  that generative AI can do, and it,
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  and it, it certainly has captured our imaginations.
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  And, you know,
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  when we start thinking about the administrative overhead
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  that is so, uh, problemsome for people
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  inside of medicine, the, the opportunities to have an AI
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  to help address the issues is just amazing.
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  So I, I, I think there's, there's lots of great excitement.
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  The the problem is that there's also a lack of understanding
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  and that lack of understanding and knowledge is one
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  of the things we face on regular basis.
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  For instance, I mean, I, I tell you, when you start to look
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  at, at ai, you know, we, we have, we have, um, execs
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  and we have users who come up to me
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  and say, well, we need AI to solve, you know, to help us.
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  And I, I guess the, the issue that always comes up is
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  what we, we need to do is, is to understand what the nature
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  of the problem is around whatever issue there is that they,
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  they they want AI for, and then decide whether
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  or not AI is the right approach to help address the issue.
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  I mean, AI is a tool like many other tools that we have.
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  I tell you that most of the AI
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  that we've looked at is a very expensive tool,
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  and that expense, you know, can, can help inhibit the notion
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  of it being adopted or, um, by our organization.
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  I think we have to be very careful.
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  Um, when I start to talk to users about all of the issues
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  that are out there, there's, um, there's almost a hesitancy
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  for me to actually make those kinds of statements.
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  You know, there's so many people that just want
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  to plow ahead without thinking about the, uh, the dangers
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  and the issues that are out there.
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  I think we, we have to approach AI with caution,
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  with some notion that we have to, you know, make sure
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  that it's proven and we have to make sure
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  that there are very defined metrics for its use
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  before we, uh, before and, and as we adopt.
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  - That's such a great point.
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  Thank you so much for sharing just your thought process
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  there, and especially how other clinicians are,
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  are viewing AI and, and technology integration in general.
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  Now, I know we've talked about a lot
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  of different changes within the healthcare space
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  and how it's evolving so rapidly.
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  What do you think is going
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  to be the most effective thing healthcares will need
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  to be successful over the next two to three years?
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  What should leaders do and understand,
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  and what will they need to do, um, to make sure
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  that their organizations are successful?
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  - So, I, I would tell you that, that when I start to talk
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  to my colleagues, uh, around the, the, uh,
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  the country, a lot
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  of them are facing the same kind of things that we're facing.
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  There's, um, uh, revenue challenges,
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  and I, I think a lot of healthcare organizations
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  have since, uh, since Covid, they, they've,
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  they've really had to, um, rethink of
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  how they can reduce costs, improve quality,
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  and do so in a way that, uh, can, can somehow promise all
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  of this at a lower cost.
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  I think that those, those issues are paramount to a lot
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  of the organizations and,
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  and a lot of people, uh, I,
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  I do think there's gonna be a continual, uh, focus on
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  how do we improve the quality of the work that we provide.
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  Uh, I'm just seeing that more
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  and more often as, as I talk to people,
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  those quality initiatives are becoming, well,
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  it's not like they weren't, you know, prevalent beforehand,
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  but they're, they're becoming even more important
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  and the use of the EHR
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  and other clinical tools to help in the process
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  of delivering care, it's becoming more
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  and more, um, you know, more
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  and more of a project, more of a learning issue.
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  So I, I think that's something that, that you'll see more
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  of as time goes on.
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  Um, I would also say,
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  and when I, I, I start to, to think about the, um,
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  the issues and projects that people start to, to work on, I,
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  I do think that we are going to see more
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  and more integration across the healthcare system
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  and the healthcare environment that, that integration,
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  what I mean by that is, is more ways of integrating data
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  and operations, uh, about patients
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  and making it into a more
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  wholesome approach to patient care.
• 15:18
  I think we're gonna find that the data that patients have
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  and collect on their everyday lives are gonna start
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  to impact the way that we treat patients.
• 15:26
  Uh, I think you're gonna see more wearables in the system.
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  I think you're gonna see patients have reported outcomes
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  will start to drive the, the way we, we, uh, handle care.
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  So I, I think that's all there.
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  Um, I, I would also tell you that digital transformation
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  continues to be an issue that we start to work on so
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  that a lot of different facilities
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  that we have within the healthcare system,
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  I think are gonna be, be produced
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  or will be evaluated in such a way that, uh, they'll,
• 15:55
  they'll move to digital tools.
• 15:59
  - That's fascinating to hear.
• 16:00
  Dr. Weiss, thank you so much
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  for joining us on the podcast today.
• 16:02
  This has been such a fun and fascinating conversation,
• 16:04
  and I look forward to connecting with you again soon.
• 16:07
  - Sounds good. Thank you very much.
• 16:12
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• 16:14
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