Sara, welcome.
In your view, where are we seeing digital approaches having
the most impact in health care delivery?
So I work with a provider, and I think there's certainly, you
know, we actually have 5A's of AI.
We talk about assisting, augmenting, automating,
accelerating, and amplifying.
And I think those all apply in our scenarios.
We've seen the most amount of, I would say, impact on the
clinician experience and on the patient experience.
And there's, of course, a lot of overlap between the two, and
they intersect quite a lot.
A couple of examples.
We are seeing a tremendous amount of potential as it
relates to digital to drive a better consumer experience
around what our Providence promise is: which is know me,
care for me, ease my way.
So number one: know who your users are.
It's really critical to know who your users are.
And we've done a pretty poor job
of that in health care historically.
It's very episodic.
It's very, like, you got sick, you came in, that's all we know
about you.
But now, digital has the potential, in particular through
new identity approaches, approaches that are much more
cohesive across a full digital ecosystem--not just limited to
one specific organization.
We can actually know people across all the things that
matter to them and then deliver personalized experiences.
So I think that is one really tremendous area that we're going
to see a lot of movement on in the next couple of years.
The other big areas are on clinician experience.
So I think these are still kind of low-hanging fruit, a lot of
basic blocking and tackling as it relates to things like
Ambient--support for documentation--and charting for
clinicians in basket management.
If you're not familiar with the concept of the in basket, it's
basically a physicians e-mail inbox.
It's their work queue that's in Epic, and they have to touch
thousands and thousands of messages, which is grinding away
at physicians and APPs and
making their lives really difficult.
So actually understanding the context of messages, both in the
clinical context--sort of more generally as to what an
appropriate action would be--but also that specific patient and
then supporting them in driving a specific action.
So similar to the consumer personalization side, but much
more focused on physicians and APPs.
And I think all of those things, you'll notice similar
themes, right?
Know what the context is, deliver insights, and then be
able to take action.
And those common themes are going to become more and more
widespread with the improvements in technology.
Last thing I'll say is a bit of a caution and thing that I worry
about is that over the last eight years or so, we've seen a
massive proliferation of solutions.
And I know we'll talk a little bit about the challenges, but
that we can't repeat that same pattern because providers are
already overwhelmed.
It's just we should learn from our mistakes.
What do you see as the main stumbling box to realizing those
potentials for both patients and clinicians?
The difficulty in separating out signal from noise,
especially with GenAI solutions
or LLM--large-language model--powered solutions
is very real.
And the reason for that proliferation of solutions and
the difficulty of differentiating signal from
noise is because it's actually gotten really easy
to build applications.
It's like I could do it, and I'm not a technologist, right?
There are so many tools out there for building applications,
but then how do they integrate into the workflow?
How do they integrate into the
underlying technical infrastructure?
How do you monitor them on an ongoing basis to make sure
they're doing the thing that you want them to do and that you
think that they're doing?
Are they actually working?
And by the way, do they share the data?
Do you have the visibility to even be able to do monitoring in
the first place?
So those are some of the big challenges that we're seeing:
massive proliferation.
And so it's just a massive sea change in how easy it is to
build something.
But then what's the value?
What are you getting for it?
Finally, what are some of the trends, the innovations that
you're most excited about for the year ahead?
I'm very excited about a few things.
One, and it sounds like probably the least exciting thing, but I
love infrastructure, and I think it has so
much potential to transform.
health care . . . is everything that's being done in monitoring.
What do you need to do to test and validate a model from an AI
context before you ever deploy it?
And at what point is it a snapshot in time?
The model, the second you release that model out into the
wild it starts to change.
And so how we think about monitoring from a predeployment
perspective and then from a postdeployment perspective, it's
. . . there's things called model drift.
You need to ensure, you know, all of these models, the
outcomes, the outputs are what we call probabilistic,
not deterministic.
So you don't get a single output for the input that is always
going to be the same.
There's virtually an infinite number of possibilities
within a range.
And so how you do that work is, I think, very interesting is
very interesting technical problem, how you do governance
around it from a data, you know, training set perspective, a
provenance perspective.
I think all of that is extremely exciting, even though it's the
the sort of nerdy technical stuff.
But what it really like the output of that is if we don't do
that stuff, we're not going to responsibly deploy AI, and we
will be held to account with our patients, with our clinicians,
in the court of public opinion, even at the state and
federal regulatory level, even with some themes around
deregulation at the federal level.
So I think we have to do that, and I'm very excited about it.
And then ultimately, I do think that this is a major inflection
point as it relates to being able to achieve the quad aim in
health care.
Bringing down costs has been really hard, right?
It's because complexity has increased so much. And we can
actually take complexity out and reimagine the way that health
care is administered,
in addition to the way it's delivered.
We often talk about, oh, you know, you know, these sort of
things that influence clinical delivery, but I think that the
other stuff actually is really powerful too--just how you
administer a system that is so complex and make it really easy?
And I think that AI might allow us to see new things as well:
new patterns, new ways of delivering without, you know
one of the challenges have of technology has always been,
well, you need standardization first.
I think that we can see new ways of delivering care in a hospital
with and it just administration of care as well with GenAI.
Sara, can you give me an example
of how this benefits patient outcome?
Yes, absolutely.
So, think about you as a user.
You're different from me as a user.
We are, we live in different parts of the world.
We have different families.
We have different clinical needs and probably different social
situations as well, like you might have, you might live in an
area with public transportation, I might not.
And so when I talked about knowing the user, for
instance, think about if you logged into your experience, it
was tailored to you, your clinical provider, your
physician is at the top.
The actions that you specifically need to take. Let's
say you need to go in and get immunized, and I need to go and
do a mammogram. We’re different people.
And that one thing that you have to do is tailored specifically
to you and delivered specifically to you versus what
I need to do is tailor specific to me and deliver specifically
to me and in the way that we want.
So you might want to access via mobile, I might want to access
via web, or I want someone to text it to me.
And so knowing those individual things drives better outcomes.
And what we know today is that when we have personalized
insights that are delivered to our patients that it's just the
next thing you have to do.
It's not the long list, the 25 things you have to do.
It's just the one thing that we drive, what's in very sort of
plain terms is called better conversion.
We know that folks will engage and when they engage their
outcomes are better.
So that is a really plain example of people getting the
for instance, the preventive care that they need just because
it was made easy for them to understand and presented to them
where they are.
Sara, thank you so much.
Thank you.