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This is Laura Dirda with the Becker's Healthcare

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I'm thrilled today to be joined by doctor

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Deepti Pandita,

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vice president of informatics and chief medical information

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officer at UCI Health. Doctor Pandita, it's a

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pleasure to have you on the podcast today.

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Thank you, Laura, for having me on.

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I'm excited for our conversation because I know

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there's a lot of cool things you're doing

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there at UCI Health, and certainly we'll be

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excited to learn a little bit more about

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how you're thinking about the future as well.

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But before we dive in, I'm wondering, can

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you tell us a little bit more about

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UCI Health and what makes it unique?

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Yeah. Absolutely.

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So UCI Health is part of the University

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of California Health Systems.

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You as you know, University of California is

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a large academic

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organization,

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and we have several universities.

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However, we have five health systems affiliated with

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our and

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University of California Irvine is one of them.

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We are,

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six hospital system currently, five operational one that

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we are building and will be operational in,

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December of this year, and then we have,

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perhaps another rehab hospital in the works for

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next year. So we are soon to be

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a seven hospital system.

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We have a very large ambulatory footprint as

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well. We see about 1,200,000

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ambulatory visits

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every year,

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apart from what we do in the inpatient

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space. And then we have multiple emergency departments

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as well.

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Great. That's amazing to hear, you know, and

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what an important community that you're serving,

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in Irvine.

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From your perspective, what is the accomplishments that

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you're most proud of from the last year?

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Yeah. So there are multiple, but I I

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would say,

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I would

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sort of proud to share two accomplishments. One,

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I have been here close to about,

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nearly two years now. And when I got

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here, there was no clinical informatics structure.

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Or if there was one, it was completely

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broken. So,

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in my mind, you know, clinical informatics is

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that sort of translator role between

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operational speak and clinical speak versus IT speak.

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So,

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getting that,

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structure up and running was my first task,

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and I'm proud to say that we now

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have a very, very functional

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clinical informatics division within ITS.

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The other big accomplishment is with all the

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acquisitions we have had,

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meeting the needs of our provider and,

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clinical communities,

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because we now currently have disparate systems, and,

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we have made the decision that we are

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gonna bring everyone onto one system.

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And just leading all the dis all the

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disparate systems,

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and the com the workflows and all that

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into one

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system has been challenging, but also rewarding in

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many ways because it is also

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what is going to align our cultures together.

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So whether a patient goes to any of

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our hospital sites or any of our ambulatory

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sites, the patient experience is a UCI experience

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and not an individual hospital or clinic system

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experience.

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That's amazing to hear. And, you know, I

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can imagine,

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easier said than done. And just a huge

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feat to bring all those different, hospitals and

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systems together into,

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that one,

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integrated

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EHR system for one, but then two, just

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the cultural side of things. Is there anything

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from your perspective that you've been able to

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do well to, make that process as seamless

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as it can be?

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Yeah. I am a very big stickler for

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governance, and I think the biggest accomplishment

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has been,

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you know, promoting the value of governance to

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all the stakeholders

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in the whole process,

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because,

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you know, people were doing governance in their

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own silos. And the

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what I have been able to accomplish is

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show them the value of shared governance

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and shared decision making

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and transparency in governance so that we are

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actually able to be more nimble in our

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decision making and also,

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be able to,

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drive decision making more, in a more coordinated

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manner so that everyone is on the same

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page and then can, you know,

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abide by that decision in the future because

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they were at the table when that decision

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was made.

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That makes a lot of sense. Thank you

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for going a little bit deeper there. Now

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I'm curious. Looking into the future, where do

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you see some of the big growth opportunities

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for you and your team in the next

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twelve months

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or so?

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So I think, you know,

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the growth opportunity is the same that has

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been there all this time, which is what

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are the challenges we are facing. You know,

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all health systems are facing

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challenges with narrow margins.

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How do we make our,

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care teams more productive, more efficient, more proficient.

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And these challenges have not changed at least

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in the last couple of decades. They've always

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been there. It's just that the tools to

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meet these challenges are rapidly evolving. And,

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you wouldn't have a podcast if I didn't

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mention AI. So I think the future of

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plugging all the AI tools

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to driving more administrative

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efficiency, operational efficiency, and decreasing the cognitive burden

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of our clinical teams so they can be

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more free to provide that very,

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you know, top of line patient care is

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where everything is moving. So what I am

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excited about is how do we use

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AI in the realm of

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improving,

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efficiency and proficiency for our clinical teams.

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That's fascinating to hear. And, certainly,

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having the AI

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opportunities with the, more broad clinical teams, I

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can imagine, as you said, bring, some great

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efficiencies and great opportunities, but also big challenges.

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Can you dig a little bit deeper into,

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some of those challenges that you're anticipating in

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the next year or so and how you're

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navigating them?

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Yeah. So the biggest challenge I would say

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is,

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you know, AI cannot solve for broken systems

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or broken workflows.

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So if you are designing

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AI to sort of, you know, be the

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square background whole approach, it's not gonna work.

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AI tools, you know, promise efficiency gains but

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struggle when introduced into real world workflows, and

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I have several experiences of this.

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You know, physicians, nurses, other clinical care team

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members are already overwhelmed with EHR burdens.

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And if the AI tool doesn't seamlessly integrate,

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into the workflow, it's gonna, you know, meet

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resistance and it's going to fail.

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So my role is how do I make

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successful AI implementations that are almost invisible,

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which means that they feel like a natural

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extension of existing workflows rather than adding,

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additional burden.

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And how we do this is, you know,

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again, having governance frameworks,

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you know, that

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can provide explainability of the AI tool or,

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you know, accountability or

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ownership of the tools,

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to make sure that there is trust and

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compliance with the tools.

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And then the other thing that's happening

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is ROI is being overestimated of these tools.

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There is a lot of hidden costs of

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AI, including, you know, workflow,

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training,

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accuracy issues,

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data science evaluations,

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and all of that.

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So,

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again, making sure that

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the ROI will come conversation is happening

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rather than, you know, falsely touting that the

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ROI is here now. And then I am

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a big, big proponent of keeping a human

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in the loop. So

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full automation

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is not the right solution, and keeping people

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cognizant of that

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is very important in my view.

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I think that's incredibly useful and helpful information

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to think through, especially as you're incorporating

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AI and trying to figure out the best

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ways to bring it into the health system,

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the organization, and then optimize it and and

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find that ROI that you were talking about

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as quickly as possible.

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Could you dig a little bit deeper there

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in in terms of, what are those conversations

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look like? What do you have to continuously

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think about and check-in on as you're starting

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to implement new technologies or AI into different

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workflows,

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to make sure your that message isn't getting

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lost and that ROI is actually being realized

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and you have a, a, aligned understanding of

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how, that will come in the future?

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Yeah. That's a great question. So let's take

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the example of AI Scribes, which I think

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every health care system is looking at and,

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you know,

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decision support automation tools that save clinical

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time,

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the actual ROI depends on adoption,

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ongoing maintenance, and integration costs. You know,

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the tool must be measured by real world

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impact, not just theoretical

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savings.

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So the metrics

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for measuring that ROI should include clinician adoption

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rates, reducing cognitive load,

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improve documentation

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quality.

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And this is what I call soft ROI.

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It's not like a hard cost ROI.

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However,

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there is enough, you know, social science behind

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it to say, if you do all this,

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if you reduce cognitive load, if you increase

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the retainability of a clinician when they are

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less burnt out, if you improve documentation quality,

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that improved billing, improved engagement with the system,

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being able to see more patients, that hard

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ROI will come, but it's not there today.

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So having that conversation and presenting it in

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that manner is very important.

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Got it. That makes a lot of sense.

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And, you know, it's a really great and

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timely example as I know there's so many

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systems that are trying to bring in those

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AI scribes or doing something along those lines

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that,

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you know, trying to figure out exactly what

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makes the most sense and how they can

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move forward there in a meaningful way. So

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I appreciate that. Before we wrap up, I'm

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curious. What is the number one thing you're

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doing right now to set up UCI Health

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for success in the future?

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So, again, like I said, we have two,

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big projects. One is, you know, bringing everyone

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on a single EHR platform,

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which is, what we are working fast and

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furious towards,

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to be have a big bang go live

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in December.

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And the second is getting a handle on

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all of our AI suite of offerings

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and then,

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work with our EHR vendor to make sure

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that we are highlighting, leading,

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implementing

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all those solutions.

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At the same time, standing up AI governance

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frameworks,

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that, you know, assign clear accountability,

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ethical standards, compliance, and trust in those systems.

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So there are two parallel things going on

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there.

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Got it. Absolutely. That is fascinating to hear

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about. And, you know, I I think especially

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looking at AI governments governance and those frameworks.

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I know you mentioned that's something that you

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really,

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dig deep into and that is really passionate

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about that governance. So,

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something that I know as well a lot

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of health care leaders mentioned to me, but

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they haven't figured out how to do it

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right on their end. Just before we wrap

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up, is there anything any advice you'd have

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for them as they're developing AI frameworks, with

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their broader teams and truly trying to make

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sure they're hitting all the right notes so

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they don't have to go back and revise

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too much in the future, but really truly

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have a a strong standing to move forward?

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Yeah. So my my,

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advice would be, you know, AI implementation

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is not just about the model. It's not

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like reaching out to the vendor and getting

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an AI model. It's still at the heart

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of it, goes back to the key principles

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of informatics, which is people, process, and policy,

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and

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technology.

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So the systems that will invest in clinician

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buy in, robust AI governance

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with multi stakeholder presence,

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workflow integration, they are the ones who are

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gonna see success in deployment of AI

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and expect

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gains rather than systems that are just implementing

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AI

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because,

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you know, it is available.

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Got it. That's such a great point.

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Thank you so much again for joining us

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on the podcast today,

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doctor Pandita. It's been a true pleasure connecting

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with you and, hearing from you today, and

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I look forward to speaking with you again

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soon. Thank you so much, Laura, for having

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me on.