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Hello, and welcome to the Becker's Health Care
podcast recorded live with the 9th annual health
IT digital health and RCM conference. I'm joined
today by Divya Pathar, chief data and AI
officer at NYC Health and Hospitals.
Divya, to get us started, can you please
tell us a little bit about yourself, your
background, and your role at your organization?
Absolutely. And, first of all, thank you for
this opportunity. My name is Divya Pathak. I'm
the chief data and AI officer at New
York City Health and Hospitals, the largest public
health care delivery system in the country.
I have over 18 years experience
in data, AI, and analytics
in health care, and I've worked with with
variety of diverse stakeholders
across health systems, academic medical centers,
payers, digital health, and pharmaceutical
companies.
Perfect. Well, AI adoption is exploding in health
care right now. In your view, what's the
most significant or promising application of this technology
right now, and how is this informing your
organization's innovation strategy?
I agree. AI adoption in health care is
rapidly advancing, and we are seeing a significant
impact on both the clinical and the nonclinical
areas even within health and hospitals.
On the clinical side, AI powered decision support
systems and personalized care models are enhancing the
diagnostic, the treatment plans, and patient outcomes
by
integrating complex data sources like the medical records,
the imaging, and the genomic data that provides
us a vast opportunity to actually understand the
patient population
and also serve the patients better.
Ambient listening technology is another one that we
hear quite a bit, recently that's actually
has multiple
efficiencies in terms of reducing the documentation burden,
improving the patient experience,
leading to better scheduling optimization
for the patients,
and most importantly, reducing the clinical burnout. And
we're seeing a lot more focus on that
in our systems.
On the nonclinical
side, AI is driving major efficiencies and revenue
cycle management
by streamlining
streamlining
billing claims and optimizing revenue.
Additionally, we've started using AI to support workforce
management, provide predictive maintenance, and improving the overall
operational efficiencies on the non clinical areas. To
me, I think these advancements are not just
shaping the industry, but also shaping New York
City Health and Hospital's innovation strategy
as we're trying to focus on
care delivery, improved care delivery, and operational efficiencies
and effectiveness across the whole system.
So on a daily basis, health care leaders
are managing greater volumes of data and more
devices across a growing number of care settings
and populations.
In this complex environment, what clinical data integration
tools or practices are you seeing drive improvements
in patient outcomes and operations? And do you
have an example or 2 you can share?
So if you look at today's health care
data,
according to a recent survey, it constitutes to
almost 32%
of world's data volumes.
So that's huge. So we're living in an
explosion era.
And,
thanks to all the variables and other additional
devices that's Bluetooth enabled, that increases just the
volume on a daily basis.
So it's important for us to understand the
digital presence of this data that's focused on
a patient's well-being and wellness. Mhmm. And one
of the most impact ful tools that we
have embraced within health and hospitals is
the cloud based data platform, Snowflake Mhmm. Which
is allowing us to have seamless integration of
this diverse data sources, including the EHR, variables,
and imaging data. And we're also adding genomics
to it. So these platforms not only enable
and we're also adding genomics to it. So
these platforms not only enable real time analytics,
but also enable more
personalized care delivery Mhmm. That's required to our
population.
Another example I would give from our organization
using this data platform
is how we integrate the patient, the, data
across various settings to enhance chronic disease management.
By leveraging data and predictive analytics, we've been
able to identify high risk patients earlier,
enable timely interventions,
and improve the long term outcomes Mhmm. Leading
to reduced readmissions and improved outcomes for those
patients. So this approach not only enhances patient
care at health and hospitals, but it's also
an important one to also optimize the resource
allocation across the system. Perfect. Well, how can
health care organizations better support IT and clinical
teams as they carry out innovation efforts? And,
what are some of the common pitfalls here?
I think we are living in an evolving
era where we're constantly learning how to adapt
to the changing,
situation and both in terms of the technology
and the workforce. So I think it is
important for healthier organizations
knowing the uncertainty we are living in to
foster stronger collaboration,
provide the right resources
and support of the talent needed, and more
importantly, encourage a culture of innovation and continuous
learning.
Clear communication between IT and clinical teams is
essential to ensure that the technology solutions align
with the work streams and the clinical needs,
and providing adequate training,
and change management support is also critical. So
there's a lot of cultural
aspect to also embracing AI Right. Right. In
ecosystems.
So with your experience, what's your top piece
of advice for other health care leaders as
they prepare for further advancements in technology and
greater demands for care?
My top piece of advice would be embrace
the randomness,
prioritize agility and adaptability in both in the
technology and the workforce development.
And why is this important? Because as we
look at advancements in AI, data integration and
also telehealth, it's rapidly shaping the care delivery
models. We're moving from
brick and mortar style, and thanks to COVID,
we reimagine healthcare. We've moved to more virtual
delivery models. So it's important to enable that
culture of continuous learning and cross functional collaborations.
And, it's also important to be mindful of
the growing complexity in the care settings and
the data management.
Additionally, I would say that investing in robust
data governance, which is foundational to everything AI
and security measures is very important for health
care organizations.
So balancing the technology
advancements with strong governance and clinical clinician engagement,
I think, is is a good sustainable
growth path for bringing and adopting health care.
Yeah. Well, Divya, thank you so much for
joining us today on the Becker's Health Care
podcast. I really appreciate the conversation. You have
an absolutely lovely rest of your day. Thank
you so much for this opportunity.
Pleasure.