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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 Shahi Manan,

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who's a Chief Data Officer
at Bon Secours Mercy Health.

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Shahi. Do, it's a pleasure to
have you on the podcast today.

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- Same here. Thank you, Laura.

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- Now I'm looking forward to
diving in to our discussion

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and really learning more about

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what you're doing at Bon
Secours to, um, stay on ahead

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of the curve and use data and information

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and technology in a better way.

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But before we dive into my questions,

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can you tell us a little bit more

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about yourself and your background?

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- Yeah, thank you.
Thank you for having me.

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This is, uh, great to be here
and, uh, talking to you today.

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Uh, so I'm the Chief Data
Officer at W Secor Mercy Health.

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And in this role I oversee
anything, everything related

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to data analytics

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and, uh, now, uh, going
into cloud platforms,

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data analytics, um, and
ai, uh, driven innovation

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and then, uh, data characterization.

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And we have data partnerships

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and, uh, uh, various, uh,
productization work, uh, uh,

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in my, uh, overview as well.

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And, um, I have been in this
role for about two years

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before this when I was with
Mass General Brigham, uh,

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in a similar role, um,
as head of engineering

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and, uh, head of innovation.

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Uh, and, uh, I've been in
the intersection of, uh,

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big data AI technology
for over 20 years now.

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And, um, over a decade in
financial FinTech space, um,

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then high-tech space for several years

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and, um, now in healthcare for some time.

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And, uh, I think healthcare
is, uh, uh, is a great space

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to be, uh, being in data

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and AI as, uh, we are on the verge of, uh,

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huge innovation cycle in my belief.

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Um, and I think it's a great time

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overall being in technology,

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but especially in healthcare,

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we are seeing the transformations

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through digitization coming
to a maturity level, uh,

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where we are gonna jump
to the next level with AI

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and innovation with data.

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So very excited to be in
this role and in this space.

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- Well, that's great to hear.

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And you know, I think you're right.

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It's such an exciting time
to be in healthcare right now

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and really being on the precipice of

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what technology can bring to this space

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and really support caregivers as well

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as the health system at large.

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I think when you look at
everything that, um, you know,

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we've seen over the last year,

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could you talk about one change
that you've made recently

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that's yielded some great results?

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- Sure, yeah. And, uh,

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before I do that, I just wanna
also talk about a little bit

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of the context of how, uh, data

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and ai, uh, is coming into
play in healthcare today.

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Uh, as we all know, the,
uh, biggest trends, uh,

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we are seeing is more and more
focus on value-based care.

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And, uh, actually McKinsey
is projecting that the number

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of patients covered in this
space will be doubling in the

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next few years, and it'll
become over a trillion

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dollar, uh, market.

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And in that space, uh, if you
look closely, you'll see data

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and analytics have huge role to play

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and the digital transformation
that I talked about.

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Uh, so the key drivers
of value-based care,

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if you look at it, are in my
mind, um, mainly threefold.

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One is, of course, uh, the value from, uh,

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better patient outcome and
having better patient engagement,

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and then overall reducing
the operational cost

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and bring in more efficiency.

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And if you think about it,
our data is at the core of all

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of these, and we can have
so much, um, innovation

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and so much, um,
enhancement of these drivers

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to data AI applications.

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And that's what, uh, i, I
think is the biggest, uh,

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value that we see from, uh, data

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and AI driving healthcare digitization

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and the transformation in this space.

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And in that context, what, um, me

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and my team are doing is
focusing on the next generation

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of data enablement

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and then, uh, specific
innovation using, uh, big data

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and AI for better patient
outcome, better engagement,

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and driving the cost down where we can

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or bring in more efficiency.

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The one thing that made a big
difference in my view is we

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put out a new multi-tenant,
uh, big data cloud,

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uh, analytics platform that is

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consolidating not only
our clinical and EHR data,

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but all system data

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and helping to build that
longitudinal patient 360 view

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and connecting it with
other, uh, clinical as well

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as operational supply
chain, hr, uh, billing,

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financial, all information together, uh,

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to drive better insights.

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And then we already have,
um, are seeing the value, uh,

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coming out of it with, uh,
various types of insights

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and analytics that we are
helping out across the system

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to drive better operation

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and also have, um, six to
eight AI driven use cases

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that are in production based
out of these, uh, data assets

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and these analytics capabilities.

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So we are very excited about that,

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and we certainly have
a plethora of use cases

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and application areas
utilizing these platform

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data and analytics.

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- Well, that's great to hear, you know,

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and certainly exciting that,
um, you're able to, uh,

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really utilize that data platform

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to make such a difference
within the workflows and,

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and see the information,
um, that, you know, uh, is,

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is flowing throughout the health system.

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I'm wondering especially,
you know, for, uh,

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as you're looking at the
data and the information,

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how do you effectively communicate that

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with leaders of different departments?

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And then how does that information
flow down to be as, um,

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I guess make a difference in,
in become actionable items,

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um, within the organization?

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- Yeah, great question.

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I think, um, you know,
this is such a large space

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and it touches pretty much
any and every department

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and every key stakeholders,
key players, uh, leaders

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in, um, in a system like ours
and in general in healthcare.

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So you're right, the big part
of it is that, uh, evangelism

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that can help develop the
strategy that covers across,

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uh, departments across our system

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and to build that vision together

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that can help everyone align,
uh, on this value proposition.

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And that's what I have been
my team have been focused on

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over the last few years.

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And we made a great stride
by building out our roadmap,

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not only our roadmap,

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but also, um, building
out the capabilities

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that I was mentioning
and demonstrating value.

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And I think three things
come into play when you want

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to have that alignment across leaders

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and, you know, large
system across departments,

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and then adaption for data ai
and the application of those.

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And, um, not only development of those,

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but actual operationalization
of those which are

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building the vision, building
the vision and strategy,

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and then building the roadmap

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and execute by demonstrating value.

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And we have been very on that

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not only building the foundation

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and building the long-term
goals and capabilities,

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but also demonstrating value
incrementally in a three

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months, six months period at a time.

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So what that does is it
helps people understand

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and process the strategy
and the long-term goals,

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but also helps build the credibility

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by actually showing the results

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and actually demonstrating the value.

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So that's how I think we have a good run

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and, uh, we are focused
on doing more with, uh,

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larger collaboration across the system.

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- That's great to hear and
certainly an exciting time

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to see all that evolve.

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Now, I think when you zoom out
into healthcare in general,

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what are some of the top trends

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that you're following right now?

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Um, what is top of mind for
you as you're going about,

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um, planning for the future?

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- Yeah, um, great, great time again, uh,

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to be in healthcare

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because of those reasons, um, that, uh,

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there are certainly
exciting things happening

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and a lot of trends in technology as well

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as overall healthcare transformation.

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Uh, so the top ones I would
start with certainly is, uh,

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on the technology side.

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Uh, we see more and more machine
learning, um, data driven,

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uh, various capabilities, uh,
from realtime alert system

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to personalized medicine to, uh,

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more customized patient
360 driven patient care,

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uh, which certainly is, um, you know,

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improving patient's experience,
improving various outcomes.

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Uh, for example, we, uh, have rolled out

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the risk stratification
for patients to have more

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targeted care for certain
risk, uh, patients in COPD

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or in behavioral health or CHP
and now in diabetic patients.

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And that certainly, uh, can,

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and, uh, we are seeing that
result in better outcome from

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the patient's per uh,
treatment perspective.

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And then we are, uh, able
to focus on more, uh,

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understanding better
diagnostics, early detection,

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uh, and then building out
real time alerts on various

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operational levels.

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For example, uh,

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during covid time we rolled
out the real-time monitoring

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of our bed sensors

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and then extended it to
various supply chain, uh,

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related items, which was very critical.

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And that is, that trend
is ongoing on various

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other operational areas.

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So all these are, I think,
um, enabling the system

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to be more efficient and more
focused on patient engagements

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and better patient outcomes.

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So all in all,

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I think the biggest trend
is these machine learning

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and data driven various applications.

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And the latest one of course,
uh, you probably hear it in

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all conversations is the
gene AI applications.

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So I think that is also gonna
pick up a lot, uh, in terms of

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handling and managing the patient's, uh,

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unstructured information, uh,
building out better chat bots

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that can interact with the
patient, uh, more like WebMD,

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you know, at your fingertip anytime, uh,

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and various other gene AI

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and, uh, LM driven innovative
technologies evolving

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that's gonna grow bigger.

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Uh, so those are, I think
some of the top ones,

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but overall, um, the
adoption of machine learning

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and uh, AI driven applications
is, uh, certainly, uh,

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in the top of all of these.

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- That's really cool to hear.

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And definitely, you know, super exciting

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to think about the possibilities
once you've got, um,

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harnessing that artificial intelligence,

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large language models and
can really adapt it broadly.

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Um, you know, the idea

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of personalized medicine is
particularly exciting as to

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what it can really bring to
that healthcare experience, uh,

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especially when you're
looking at the next 12

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to 24 months or so.

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What does growth look like for
you within the health system?

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How do you really see your teams

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and yourself, um,
expanding the capabilities?

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- Yeah, sure.

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Um, I, I think with the new,

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or kind of I would say
more, um, upgraded version

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of our platform where we can enable more

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and more, uh, independent
data science teams or more

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and more other, um,
independent organizations

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to enable their analytics activities

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and innovation activities is gonna be big.

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So we call it, um,

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self-service democratization,
uh, environments.

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So anyone who doesn't
have the full cycle of,

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uh, technology expertise

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or full uh, stack of, uh,

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talents in-House would be able to come

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and, uh, play with the data

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and innovate with their
ideas on our platform

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and would be able to,
um, we would also be able

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to integrate their data

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and provide it in a
more meaningful fashion.

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And not only that,

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we would also look at
operationalizing the artificial

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intelligence capabilities
that we have built

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and shared the goodies with
larger, uh, group of, uh,

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hospitals in internal

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and potentially external eventually.

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Uh, we haven't fully opened
up to the external yet,

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but the platform, the capabilities

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and the innovations we have
are moving towards, uh,

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enabling, uh, US to do that.

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And I think that will
be a big jump in terms

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of our services, in terms
of our value extraction.

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I'm super excited about that,
that, uh, this multi-tenant,

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uh, and information
asset is gonna help us,

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uh, with that path.

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The other part is we are

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actually continuously working
on several use cases that are

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in those three key areas

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of value-based care that I mentioned.

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And, uh, our, um, teams are
working hard to add those

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to our, um, capability

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and application areas,
uh, over the next year

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and we should see more and
more, uh, application and value

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and adoption of those.

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Um, the last one is we are also
partnering with various, uh,

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other systems, other data

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and technology partners
for more innovation,

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more revenue generation
generating opportunities.

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And those I think would be
also coming to the next level

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of maturity for, um, revenue generation

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and value extraction.

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So exciting and busy time ahead.

286
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- Absolutely. For sure. You
know, it seems like, um,

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so many opportunities and
ability to, um, jump in

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and really transform the way
healthcare is, is moving.

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And in particular, when you
think about those value added

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opportunities or revenue
generating, um, areas, you know,

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what does that really look like?

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What are some of the, I guess
the discussion points when you

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look at how, um, you
know, you can continue

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to add value in revenue to
the organization overall?

295
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- Uh, sure. Yeah. So I'm gonna
give a couple of examples.

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So one is that, uh, we have
actually, um, also, uh,

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with the team and some

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of these technology partnership solved out

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and built in the capability to
de-identify our patient data.

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We are extremely, um, uh, uh, cautious

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how we handle our data,
respecting the privacy

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of our patients and, uh,
being compliant with HIPAA

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and other regulations.

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But, um, this de-identification

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and anonymization
technology has enabled us

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to share the data for more innovation

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and revenue generation.

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So that's certainly something
that, um, has also, uh,

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helped us build the partnership with some

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of the technology companies
who are focused on,

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uh, targeted innovation.

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Uh, for example, we are working
on building out a chat bot

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that, uh, helps, uh, patients, um, respond

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to their questions

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and queries, uh, real
time anytime of the day.

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It's like, uh, WebMD on a chat bot.

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Um, that can help, uh,
with patient engagements

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and patients' understanding,
um, of the situation

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or the problem and guide them

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for the next steps, uh, instantly.

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We are also looking at using
LLM for nurse triaging, uh,

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for better efficiency and
again, better patient engagement

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and, uh, experience.

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We are looking at various, um,

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operational machine learning
driven applications.

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Some are already in
production for, uh, reducing

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or optimizing hospital stay length of stay

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or, uh, predicting hospital readmission

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so we can better take care
of those high risk patients.

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So all these are in play

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and some of those through
partnerships or innovation

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and productization, we are
hoping will earn our, um,

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more revenue and, uh,
expedite some more innovation

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and some will extract more
value by cost reduction

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or optimizing our operations.

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Um, and there are, these
are some of the, I'd say top

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of the iceberg, uh, high value
items that we are focused on,

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but we are constantly
looking at more opportunities

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and we have, uh, you know, built
out kind of a queue of, um,

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a next set of use cases that
we'll continue to work on.

341
00:17:45,185 --> 00:17:46,245
- That's amazing to hear.

342
00:17:46,315 --> 00:17:48,845
Well, thank you so much for
joining us on the podcast today.

343
00:17:48,935 --> 00:17:51,765
Shahi, do. This has been
a really fun discussion

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00:17:51,765 --> 00:17:53,485
and I look forward to
connecting with you again soon.

345
00:17:54,175 --> 00:17:56,485
- Thank you. It's been
great, uh, talking to you

346
00:17:56,665 --> 00:17:58,525
and a pleasure being here.

347
00:17:58,615 --> 00:17:59,525
Thank you for having me.