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Philips is a health tech leader focused on

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innovation that improves the health and well-being of

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people. Our health care technology and informatics solutions

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help care teams diagnose, treat, and manage more

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patients with greater precision, speed, and confidence across

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the care journey. With Philips, clinicians are empowered

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with streamlined insights in the moments that matter

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for every patient. Better care for more people.

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Philips.

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Hello, and welcome to the Becker's Healthcare Podcast,

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recorded at the 9th Annual Health IT Digital

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Health and RCM Conference. I'm joined today by

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Tino Tedeshe, associate chief medical information officer at

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University Hospitals Health System.

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Tinu, to get us started, can you please

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share a little bit about your background, your

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organization, and your role at that organization?

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Thank you for having me. I'm excited to

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be speaking at this podcast. My name, like

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you've heard, is Tinu Tadeshi, and I am

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associate CMIO at University Hospitals.

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I have responsibility

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for the community hospitals.

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My background is pediatrics. I'm a general pediatrician.

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A few years ago, well, over a decade

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now, I decided to go into informatics,

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and I have worked for a health IT

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company. I did that for about 6 years,

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helping with design and, different things touring the

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United States,

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helping implement,

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EHRs

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across the country.

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About 6 years ago, I decided to get

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off the,

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just

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the hustle and bustle of traveling and became

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a a VP of clinical informatics at Lake

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Health System,

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in Ohio.

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That system was acquired by University Hospitals,

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and I am now an associate CMIO,

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for community care,

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and regulatory.

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So from a 3 hospital system, I became

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responsible for,

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12 hospitals.

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So right now, that's what I do. We,

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continue to work to improve our informatics

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team.

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Perfect. So as I'm sure you're aware, you

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know, AI adoption is exploding in healthcare right

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now.

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In your view, what's the most significant or

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promising application of this technology right now? And

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how is this informing your organization's innovation strategy?

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Indeed, AI is exploding. It's exploding in such

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a way that everywhere you turn it is

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AI.

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Well, so, about 2 years ago, you know,

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it was like, oh, AI is going to

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come and the question is,

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do we wanna embrace it? What does that

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mean for patient data? Is it gonna be

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secure and so on?

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Are we gonna have are we gonna be

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infringing on patients' right, their data, and so

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on?

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Right now,

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it's in everything.

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EHR

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has it in every way you can think

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about for patient access.

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It's in our documentation.

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It's in our revenue cycle.

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That's one of my specialties rev cycle as

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well.

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So we are using it in every which

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way,

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trying to see how can we simplify,

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what we do on a day to day

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basis for our clinicians

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and also for operations.

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So we we are also using it in

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our

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rev cycle,

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managing denials,

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interacting with payers,

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also using it for physician documentation. We're using

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it in a lot of ways. I can

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go into details if you want me to.

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Go for it. Yeah. Yeah. Yeah. Alright. Well,

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I guess my first interaction with AI really

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was about, 4 years ago when we started

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to use AI in the area of,

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physician documentation.

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When you think about it, there is a

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lot of data. There's a lot of regulation.

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There are things

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physicians need to do to be able to

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make sure that they're,

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paid for the services they've rendered.

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Rev cycle being one of my passions, we

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started to look at the business of care,

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how can we assist

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our physicians

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to reduce the burden? How do you remember

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all these things you're supposed to document to

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be able to be paid for a certain

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DRG?

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And,

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so what we did was we partnered with,

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another,

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well, we'll call it a 3rd party and,

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just to give our physicians some help at

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the point of care. So while they're documenting,

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they start to get nudges as to you

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mentioned this patient had chest pain,

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and it looks like you're going towards this

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diagnosis. Were you thinking of mentioning this? We

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do not see this in your notes. Do

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you wanna do that? Mhmm. And not leading

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them to a diagnosis, but if you've made

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a diagnosis

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and you've, you know, talk, thought of 1

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or 2 things to complete your,

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your documentation,

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we started to see do that, and we

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started to realize almost immediately a return on

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investment. So case mix index within a month

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went up for specific

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service lines. So that was my first interaction

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with AI,

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machine learning, large language models, just doing that

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at the point of care, being able to

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use

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what AI can do to reduce the burden

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on the physicians and yet get paid for

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it. And then as things progressed, we started

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to realize we could use it in so

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many ways. So after we merged as a

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health system

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with university hospitals, university hospitals being one of

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the greatest health systems I can think of

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in the United States,

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they already had things. So even last year,

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they started to,

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they got a grant where they're being able

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to, do predictive analytics on cardiovascular

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disease Oh, wow. Using large language models. We

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have just been recently,

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given a badge,

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for our radiology department

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for quality in AI. So there's a lot

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we are doing with it, and it's just

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exciting.

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Of course, we are newly implemented.

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EHR now has AI in every nook and

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cranny of it. Mhmm. It's exciting. It's an

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exciting time. Yeah. Well and and I'm curious.

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You know, so you've been working with AI

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for a while. How has your overall view

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and, you know, understanding about what what what's

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possible with AI and the expectations around that?

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Like, how has that evolved over your time

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working with it? So

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initially, when I first started with this, it

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was like, wow. This is amazing. Now Mhmm.

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Let's talk about it. In in the amazing

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way it is, it's the adoption was a

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little hard. Right. So

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providers,

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or physicians are really used to their autonomy.

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They wanna document what they wanna document.

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I, being a physician, know I wanna scribble

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2, 3 lines, do my Mhmm. Medical decision

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management, just put it in there and go.

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Well,

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our payers were not gonna pay for that.

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And and so I saw how that was

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able to elevate

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not just the documentation for patient care, but

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how we got reimbursed in in a very,

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I mean, it was like night and day.

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So Right. I thought, okay, that that's not

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bad.

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Mhmm. And then now starting to think about

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it, how do we do change management

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to bring this

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not just to the physician, but to nursing

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and and to rev cycle?

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So I saw,

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how wide we could go and how deep

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we could go,

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and the turnaround

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in implementation

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was so short

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compared to when we first started. Mhmm. It's

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it's just so everything is in the clouds

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now. Right. And you can something that would

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have taken me 6 months to implement will

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take 4 weeks now. It's amazing. Right. Right.

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It is amazing. I can I can understand

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your excitement now?

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So, you know, on a daily basis, health

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care leaders such as yourself

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are managing greater volumes of data across, a

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growing number of devices and care settings and

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populations.

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In this complex environment, what clinical data integration

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tools or practices are you seeing drive improvements

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in patient

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outcomes and operations?

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And, can you share an example or 2?

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Yeah. So I I would say analytics

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would be the place I wanna go with

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that. Mhmm. You have all this data.

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That's the one thing about implementing the EHR.

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I was involved with the meaningful use, getting

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Mhmm. Hospital systems from paper

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to electronic medical records. This was exciting, it

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was hard, but we did it. Now you

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have all this data.

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And if you are in an IDN or

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complex organization

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like I'm in, the question is how do

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we reconcile

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all this data and how do we bring

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the standardization

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or what what we call systemness

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across the whole

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health system? As you start to think of

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various hospitals,

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academia and community hospitals and the small,

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critical access hospitals, how do you bring that

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systemness

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without losing

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the uniqueness of each one? So

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having

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huge data, but that it goes through

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analytics.

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For me, that's where it all works. I

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have an operational background as well. So when

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we start to pull

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pull data out and start to determine how

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do we decrease our length of stay, how

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do we increase our CMI across service lines,

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that's where I start to use it. So

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integrating tools that will help you

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use that data in an operational way that

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would make

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decision making very easy. Right. Or

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my patients are going to various health systems

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other than my health system. Mhmm. Some are

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going for cardiovascular

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care even though we do have a great

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center,

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they're going elsewhere. When they go, how do

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I see their data? So health information exchange,

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making sure,

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that we have the tools that bring in

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the data from,

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from wherever they go. In Ohio we have,

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especially where I come from in Cleveland, we

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have a lot of our patients flying

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to Florida,

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you know, when the weather is not as

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nice.

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How do I get that data? They come

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back, and how do I use that data

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in their day to day care? So

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we have to integrate these tools.

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Mhmm. So health and then clinical decision support

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is another one. A lot of EHRs right

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now have it, but it's clunky. Right. So

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how do we streamline it, make sure it

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it makes sense to the clinician, to the

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physician at the point of care? These are

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all tools that are available, but how do

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you adopt it, Adopt them and use them

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in a way that makes sense. Right. Right.

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And so how can health care organizations and

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health care leaders

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better support IT and clinical teams as they

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carry out some of these innovation initiatives?

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And what are some of the, common pitfalls

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here?

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So,

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just from my experience, collaboration

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sometimes is lacking. We're very siloed.

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IT many times is siloed

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from clinical,

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from operations. Mhmm. These are all very strong

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departments

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and,

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aspects of health care. The the way to

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make this work in this very fast changing

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environment

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is to make sure that we cross collaborate.

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Mhmm. We have to have at the table

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each time

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operations. We have to have IT there, and

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we have to have clinical there. Now one

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of the pitfalls is clinical would go. So

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one of my colleagues' physicians may go to

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a conference

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and they see all this great software and

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applications.

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And sometimes they are leaders, and they almost

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signed off. And many times, they've signed off

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on that

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without asking IT,

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one, do you already have it? Because we

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may already have it. Right. Right. We just

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may not have deployed it yet because of

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so many priorities we have. Mhmm.

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So why, well, you may say, well, my

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department will will pay for it. Think about

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that. It's not really your department because you're

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of a health system. Right. So it's all

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our money. Mhmm. It's not just your money.

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Mhmm. So the question is, do we already

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have it? A little bit more collaboration will

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make this work. Mhmm.

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And then infrastructure.

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So

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are we, as a as a leadership, are

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we invest in put in the the the

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investment where

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we've we've said we wanna go? So you

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have this great,

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vision for innovation, but what does that really

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mean? Right. It means infrastructure

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and

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and investment, not just of time, but but

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money. Mhmm. Do we wanna do that?

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So we can support

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a lot of this initiatives

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by by just thinking through collaboration,

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money investment,

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infrastructure investment,

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training,

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and having everyone at the table.

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So what is your top piece of advice

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for other health care leaders as they prepare

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for, you know, further advancements and adoptions of

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technology and greater demand for care?

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I want us to think at the very

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beginning, when we start to think about the

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new thing you wanna do or innovation,

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think about

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the change management aspect of it. Mhmm. Mhmm.

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What does that really mean?

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And if you're in a big health system,

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what does that mean when you think about

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the microcultures?

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I'll as a physician, I wanna talk about

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the medical staff. So a lot of mergers

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and acquisitions

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happening right now. So when we start to

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merge and acquire new

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small critical access hospitals

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or big,

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community hospitals,

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remember that there are micro cultures. Mhmm. How

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are you gonna manage that? Right. You have

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a great vision, but how do you bring

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everyone together?

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Otherwise, the vision will be hard to achieve

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unless change management is a strong, strong pride

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of of the planning Mhmm. From the get

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go. Right. And so, you know, as we

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wrap up this conversation,

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you know, one thing that was really obvious

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to me was just how passionate you are

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about your job and your role in kind

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of, like, technology and health care. And one

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thing really stuck out to me, and that

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was when you mentioned how excited you are

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about seeing some of these things. And and

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you you I'm just genuinely curious.

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You know, 5, 10 years down the road,

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is there a piece of technology or something

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that will be possible with technology in the

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future that you're just especially excited about?

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So I am

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excited about

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centralization.

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Mhmm.

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There are a lot of things that we

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are doing today that we're doing based on

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almost 200 years Mhmm. Of health care, of

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doing it the same way. Right. But the

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question is,

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with all the technology out there

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and many times a patient is seen by

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a physician and the physician spends 5 minutes.

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If you spend 5 minutes and you were

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scheduled for 15 minutes,

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what was it that you were able to

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do in 5 minutes?

402
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And the remaining 10 minutes,

403
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could we centralize all of that? Mhmm. Could

404
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we do it in such a way that

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somebody else picks up that aspect and does

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it centrally so that you focus on what

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you are the only person who can do.

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So we have the central corporate

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aspect of health care that is under guarded

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by IT. Mhmm. We have all the tools,

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really. Even now we have the tool. We

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just have to reimagine

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health care and how we deliver health care.

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Mhmm. And and and with that in mind,

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I am seeing that there are a lot

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of things that are repetitive, that are redundant,

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that we can cut out of, the way

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we provide health care. It's an exciting time.

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00:15:47,184 --> 00:15:49,345
Right. Right. Right. Well, thank you so much

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00:15:49,345 --> 00:15:51,504
again. This was a great conversation. I absolutely

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00:15:51,504 --> 00:15:52,945
loved it. Thank you again for joining us

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00:15:52,945 --> 00:15:54,865
today. Thank you so much for having me.

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00:15:54,865 --> 00:15:56,225
My pleasure. You have a lovely rest of

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your day. Thank you.