- This is Laura Dedo with the Becker's Healthcare Podcast.
I'm thrilled today to be joined by Shahi Manan,
who's a Chief Data Officer at Bon Secours Mercy Health.
Shahi. Do, it's a pleasure to have you on the podcast today.
- Same here. Thank you, Laura.
- Now I'm looking forward to diving in to our discussion
and really learning more about
what you're doing at Bon Secours to, um, stay on ahead
of the curve and use data and information
and technology in a better way.
But before we dive into my questions,
can you tell us a little bit more
about yourself and your background?
- Yeah, thank you. Thank you for having me.
This is, uh, great to be here and, uh, talking to you today.
Uh, so I'm the Chief Data Officer at W Secor Mercy Health.
And in this role I oversee anything, everything related
to data analytics
and, uh, now, uh, going into cloud platforms,
data analytics, um, and ai, uh, driven innovation
and then, uh, data characterization.
And we have data partnerships
and, uh, uh, various, uh, productization work, uh, uh,
in my, uh, overview as well.
And, um, I have been in this role for about two years
before this when I was with Mass General Brigham, uh,
in a similar role, um, as head of engineering
and, uh, head of innovation.
Uh, and, uh, I've been in the intersection of, uh,
big data AI technology for over 20 years now.
And, um, over a decade in financial FinTech space, um,
then high-tech space for several years
and, um, now in healthcare for some time.
And, uh, I think healthcare is, uh, uh, is a great space
to be, uh, being in data
and AI as, uh, we are on the verge of, uh,
huge innovation cycle in my belief.
Um, and I think it's a great time
overall being in technology,
but especially in healthcare,
we are seeing the transformations
through digitization coming to a maturity level, uh,
where we are gonna jump to the next level with AI
and innovation with data.
So very excited to be in this role and in this space.
- Well, that's great to hear.
And you know, I think you're right.
It's such an exciting time to be in healthcare right now
and really being on the precipice of
what technology can bring to this space
and really support caregivers as well
as the health system at large.
I think when you look at everything that, um, you know,
we've seen over the last year,
could you talk about one change that you've made recently
that's yielded some great results?
- Sure, yeah. And, uh,
before I do that, I just wanna also talk about a little bit
of the context of how, uh, data
and ai, uh, is coming into play in healthcare today.
Uh, as we all know, the, uh, biggest trends, uh,
we are seeing is more and more focus on value-based care.
And, uh, actually McKinsey is projecting that the number
of patients covered in this space will be doubling in the
next few years, and it'll become over a trillion
dollar, uh, market.
And in that space, uh, if you look closely, you'll see data
and analytics have huge role to play
and the digital transformation that I talked about.
Uh, so the key drivers of value-based care,
if you look at it, are in my mind, um, mainly threefold.
One is, of course, uh, the value from, uh,
better patient outcome and having better patient engagement,
and then overall reducing the operational cost
and bring in more efficiency.
And if you think about it, our data is at the core of all
of these, and we can have so much, um, innovation
and so much, um, enhancement of these drivers
to data AI applications.
And that's what, uh, i, I think is the biggest, uh,
value that we see from, uh, data
and AI driving healthcare digitization
and the transformation in this space.
And in that context, what, um, me
and my team are doing is focusing on the next generation
of data enablement
and then, uh, specific innovation using, uh, big data
and AI for better patient outcome, better engagement,
and driving the cost down where we can
or bring in more efficiency.
The one thing that made a big difference in my view is we
put out a new multi-tenant, uh, big data cloud,
uh, analytics platform that is
consolidating not only our clinical and EHR data,
but all system data
and helping to build that longitudinal patient 360 view
and connecting it with other, uh, clinical as well
as operational supply chain, hr, uh, billing,
financial, all information together, uh,
to drive better insights.
And then we already have, um, are seeing the value, uh,
coming out of it with, uh, various types of insights
and analytics that we are helping out across the system
to drive better operation
and also have, um, six to eight AI driven use cases
that are in production based out of these, uh, data assets
and these analytics capabilities.
So we are very excited about that,
and we certainly have a plethora of use cases
and application areas utilizing these platform
data and analytics.
- Well, that's great to hear, you know,
and certainly exciting that, um, you're able to, uh,
really utilize that data platform
to make such a difference within the workflows and,
and see the information, um, that, you know, uh, is,
is flowing throughout the health system.
I'm wondering especially, you know, for, uh,
as you're looking at the data and the information,
how do you effectively communicate that
with leaders of different departments?
And then how does that information flow down to be as, um,
I guess make a difference in, in become actionable items,
um, within the organization?
- Yeah, great question.
I think, um, you know, this is such a large space
and it touches pretty much any and every department
and every key stakeholders, key players, uh, leaders
in, um, in a system like ours and in general in healthcare.
So you're right, the big part of it is that, uh, evangelism
that can help develop the strategy that covers across,
uh, departments across our system
and to build that vision together
that can help everyone align, uh, on this value proposition.
And that's what I have been my team have been focused on
over the last few years.
And we made a great stride by building out our roadmap,
not only our roadmap,
but also, um, building out the capabilities
that I was mentioning and demonstrating value.
And I think three things come into play when you want
to have that alignment across leaders
and, you know, large system across departments,
and then adaption for data ai and the application of those.
And, um, not only development of those,
but actual operationalization of those which are
building the vision, building the vision and strategy,
and then building the roadmap
and execute by demonstrating value.
And we have been very on that
not only building the foundation
and building the long-term goals and capabilities,
but also demonstrating value incrementally in a three
months, six months period at a time.
So what that does is it helps people understand
and process the strategy and the long-term goals,
but also helps build the credibility
by actually showing the results
and actually demonstrating the value.
So that's how I think we have a good run
and, uh, we are focused on doing more with, uh,
larger collaboration across the system.
- That's great to hear and certainly an exciting time
to see all that evolve.
Now, I think when you zoom out into healthcare in general,
what are some of the top trends
that you're following right now?
Um, what is top of mind for you as you're going about,
um, planning for the future?
- Yeah, um, great, great time again, uh,
to be in healthcare
because of those reasons, um, that, uh,
there are certainly exciting things happening
and a lot of trends in technology as well
as overall healthcare transformation.
Uh, so the top ones I would start with certainly is, uh,
on the technology side.
Uh, we see more and more machine learning, um, data driven,
uh, various capabilities, uh, from realtime alert system
to personalized medicine to, uh,
more customized patient 360 driven patient care,
uh, which certainly is, um, you know,
improving patient's experience, improving various outcomes.
Uh, for example, we, uh, have rolled out
the risk stratification for patients to have more
targeted care for certain risk, uh, patients in COPD
or in behavioral health or CHP and now in diabetic patients.
And that certainly, uh, can,
and, uh, we are seeing that result in better outcome from
the patient's per uh, treatment perspective.
And then we are, uh, able to focus on more, uh,
understanding better diagnostics, early detection,
uh, and then building out real time alerts on various
operational levels.
For example, uh,
during covid time we rolled out the real-time monitoring
of our bed sensors
and then extended it to various supply chain, uh,
related items, which was very critical.
And that is, that trend is ongoing on various
other operational areas.
So all these are, I think, um, enabling the system
to be more efficient and more focused on patient engagements
and better patient outcomes.
So all in all,
I think the biggest trend is these machine learning
and data driven various applications.
And the latest one of course, uh, you probably hear it in
all conversations is the gene AI applications.
So I think that is also gonna pick up a lot, uh, in terms of
handling and managing the patient's, uh,
unstructured information, uh, building out better chat bots
that can interact with the patient, uh, more like WebMD,
you know, at your fingertip anytime, uh,
and various other gene AI
and, uh, LM driven innovative technologies evolving
that's gonna grow bigger.
Uh, so those are, I think some of the top ones,
but overall, um, the adoption of machine learning
and uh, AI driven applications is, uh, certainly, uh,
in the top of all of these.
- That's really cool to hear.
And definitely, you know, super exciting
to think about the possibilities once you've got, um,
harnessing that artificial intelligence,
large language models and can really adapt it broadly.
Um, you know, the idea
of personalized medicine is particularly exciting as to
what it can really bring to that healthcare experience, uh,
especially when you're looking at the next 12
to 24 months or so.
What does growth look like for you within the health system?
How do you really see your teams
and yourself, um, expanding the capabilities?
- Yeah, sure.
Um, I, I think with the new,
or kind of I would say more, um, upgraded version
of our platform where we can enable more
and more, uh, independent data science teams or more
and more other, um, independent organizations
to enable their analytics activities
and innovation activities is gonna be big.
So we call it, um,
self-service democratization, uh, environments.
So anyone who doesn't have the full cycle of,
uh, technology expertise
or full uh, stack of, uh,
talents in-House would be able to come
and, uh, play with the data
and innovate with their ideas on our platform
and would be able to, um, we would also be able
to integrate their data
and provide it in a more meaningful fashion.
And not only that,
we would also look at operationalizing the artificial
intelligence capabilities that we have built
and shared the goodies with larger, uh, group of, uh,
hospitals in internal
and potentially external eventually.
Uh, we haven't fully opened up to the external yet,
but the platform, the capabilities
and the innovations we have are moving towards, uh,
enabling, uh, US to do that.
And I think that will be a big jump in terms
of our services, in terms of our value extraction.
I'm super excited about that, that, uh, this multi-tenant,
uh, and information asset is gonna help us,
uh, with that path.
The other part is we are
actually continuously working on several use cases that are
in those three key areas
of value-based care that I mentioned.
And, uh, our, um, teams are working hard to add those
to our, um, capability
and application areas, uh, over the next year
and we should see more and more, uh, application and value
and adoption of those.
Um, the last one is we are also partnering with various, uh,
other systems, other data
and technology partners for more innovation,
more revenue generation generating opportunities.
And those I think would be also coming to the next level
of maturity for, um, revenue generation
and value extraction.
So exciting and busy time ahead.
- Absolutely. For sure. You know, it seems like, um,
so many opportunities and ability to, um, jump in
and really transform the way healthcare is, is moving.
And in particular, when you think about those value added
opportunities or revenue generating, um, areas, you know,
what does that really look like?
What are some of the, I guess the discussion points when you
look at how, um, you know, you can continue
to add value in revenue to the organization overall?
- Uh, sure. Yeah. So I'm gonna give a couple of examples.
So one is that, uh, we have actually, um, also, uh,
with the team and some
of these technology partnership solved out
and built in the capability to de-identify our patient data.
We are extremely, um, uh, uh, cautious
how we handle our data, respecting the privacy
of our patients and, uh, being compliant with HIPAA
and other regulations.
But, um, this de-identification
and anonymization technology has enabled us
to share the data for more innovation
and revenue generation.
So that's certainly something that, um, has also, uh,
helped us build the partnership with some
of the technology companies who are focused on,
uh, targeted innovation.
Uh, for example, we are working on building out a chat bot
that, uh, helps, uh, patients, um, respond
to their questions
and queries, uh, real time anytime of the day.
It's like, uh, WebMD on a chat bot.
Um, that can help, uh, with patient engagements
and patients' understanding, um, of the situation
or the problem and guide them
for the next steps, uh, instantly.
We are also looking at using LLM for nurse triaging, uh,
for better efficiency and again, better patient engagement
and, uh, experience.
We are looking at various, um,
operational machine learning driven applications.
Some are already in production for, uh, reducing
or optimizing hospital stay length of stay
or, uh, predicting hospital readmission
so we can better take care of those high risk patients.
So all these are in play
and some of those through partnerships or innovation
and productization, we are hoping will earn our, um,
more revenue and, uh, expedite some more innovation
and some will extract more value by cost reduction
or optimizing our operations.
Um, and there are, these are some of the, I'd say top
of the iceberg, uh, high value items that we are focused on,
but we are constantly looking at more opportunities
and we have, uh, you know, built out kind of a queue of, um,
a next set of use cases that we'll continue to work on.
- That's amazing to hear.
Well, thank you so much for joining us on the podcast today.
Shahi, do. This has been a really fun discussion
and I look forward to connecting with you again soon.
- Thank you. It's been great, uh, talking to you
and a pleasure being here.
Thank you for having me.