Hi, everyone. This is Lucas Voss with Becker's
Healthcare. Thanks so much for tuning in to
the Becker's Healthcare podcast series. It's great to
have you. Excited for a conversation on the
foundational role of accurate provider data in modern
healthcare.
Care. And I'm very excited to be joined
by Joey Soliske, director of digital health operations,
Alghedi Health Network, and Preeti Subramani,
vice president product management at Highmark Health for
our conversation today. Joanne Preeti, thank you so
much for being here today. It's great to
have you.
Yes. Thanks so much for having us.
Yeah. Absolutely.
I wanna kick us right off. We have
a lot to talk about. There's a lot
of elements to this conversation.
I wanna talk about with something very start
with something very important.
What is the single most important area where
Accurid provided data
makes a difference
within your organization?
Joey, why don't we start with you? Sure.
Yeah. So, just quick background on Allegheny Health
Networks. We're a 14 hospital system in Western
PA,
with over 3,000 physicians and clinicians, and we
have a great partner in Highmark Health. So
I know Preeti will talk about that collaboration
we have from a a payer and provider
perspective across the network.
But for us in the in the health
system lens, you know, I think the single
most important area where it matters
is in relation to the clinician
information being consistent.
And what I mean by that is it's
consistent across the various channels for how our
patients
could access our system. So whether that be
through Google, whether that be through our website
and find care, that same information about our
clinician or location should be the same. Mhmm.
And if we have if it's the same,
then it builds that trust, and consistency so
they keep wanting to come back.
Yeah. Pratib?
I think
Joey hit on a key point here, which
is trust in the information that we're providing.
And the single most important area from, our
Highmark Health insurance
perspective is that member experience and their ability
to find
compatible care options.
And one of the first things that people
do when they get their insurance
is look for which doctor is in network,
and they want to understand exactly what network
they're in, how much things are gonna cost
when they go to that doctor, how to
schedule an appointment with that doctor. So there
are a lot of information that we need
to kinda collect and bring together,
for those individuals so they can understand how
to go get the health care that they
need and use the health insurance plan that
they've just purchased.
Yeah. And I think what's very interesting about
this conversation, and and you both touched on
it a little bit, it's sort of this
this ecosystem approach. Right? There's so many connecting
pieces to this, so many dots that need
to be connected for this to be able
to be successful,
and and to be a successful approach, which
is really important. And I wanna talk a
little bit about some of the disconnects that
you're observing in this, process in itself
or then in turn also the opportunities that
it
Sure. Yeah. So Sure. Yeah. So for for
us,
it's also, you know, providers and the locations
data. Again, because I think something we
find is that there is inconsistency
even in, like, you know, some of our
branding name in downstream systems or, again, I'll
use the Google example displaying this. The patient
may go to their MyChart patient portal and
see there have an upcoming appointment at a
different facility name than what they saw on
our website and Google. So if we get
all that connected
across a different, pillars within an enterprise,
it makes that be consistent and feel easy
for our patient and members again. And so
for us, that is, really making sure
that
facilities,
departments like our credentialing department, you know, for
medical staff services
is sending their information for to us. Also
that our real estate department, they'll have the
updated facility info is sent into this, like
a platform,
that you have the reviews about your clinicians
coming in. And so when you connect all
those different areas together into one, it allows
for you to have that, I'll call it,
cohesive experience downstream then, by doing that.
And I think that the biggest opportunity, which
I know Preeti will talk about, is for
us being a pay biter or a payer
and a provider health system here is we
can really connect and have
that clinician information be as up to date
as possible for our members as well, which
we're really excited about.
Yeah. Priti, talk a little bit about that.
How important is that piece?
I think
Joey hit on it, you know, pretty well.
We know that providers are struggling with managing
their own data and the accuracy they have
with that data. Mhmm. And then from a
health insurance perspective,
we have
a multitude of providers that are in that
same boat, and we are receiving a lot
of inaccurate data from all of those providers.
And then trying to determine
what,
data is accurate, what's inaccurate, and how do
we showcase this to,
our members in the right way. And so
that that's one of the biggest disconnects upfront
in the journey
as we think about this. And we're starting
to deploy different capabilities in that space
to validate and ensure that data accuracy is
there. Then the other disconnect comes more downstream
in the customer journey when they're actually looking
for care and then trying to schedule an
appointment with that clinician or provider office
when they don't have enough information on how
to actually go get an appointment.
So they might get only, that far in
the journey, and then they can't figure out
how to schedule an appointment. Sometimes they just
give up
or if they get frustrated through that process.
And so those are both upstream and downstream.
We're trying to figure out how do we
solve that for people that
we give them the right information and we
tell them how to finish that full customer
journey so they can actually go get the
health care with that clinician that they need.
Yeah. Actually, managing that relationship is so key,
and that happens through that collaboration and and
identifying those opportunities for improvement, which I think
is is so important.
Joey, let's talk about some of the the
strategy
pieces to this and how you're achieving this.
Right? Can you share, an example of something
that's worked in terms of a strategy that
you've implemented,
that's really improved this process? And and what
are some of the things that you've learned
throughout this?
Yeah. I think there's a couple different things
that, you know, from a process perspective,
that we need to think about. Because, you
know, if you have a technology or the
connection points in place, that's great. But if
you don't have the upstream
data or information or the right operational leaders
that know where and how they request a
change and what needs to happen, then it's
not gonna be accurate downstream. So you need
to fix as well at the very start,
core process item. And for us, one of
the big buckets is, you know, annual review
of the information with operations. So how do
you do, you know, like, a yearly help
check up, you know, on your information for
your data with your clinicians, with your operators,
for locations? And is that phone number still
accurate, you know, for that primary care clinic
in Pittsburgh?
Is that clinician specialty still up to date?
Then do they, you know, do they get
additional information they want in their biography now
to display on Google in MyChart again in
member portal for our Highmark members? So the
annual review and expectation setting, having a team
who does that is important. The second point
then is how do you make sure to
make a request for a change in one
location? So as a clinician, you know, if
something doesn't look right, downstream, you know exactly
where we need to go to to make
a request for a change and that there's
service level arrangements on that change being, you
know, done by the next day by appropriate
teams in your enterprise. So, those are a
couple of the process related items we're really
trying to think through to make sure the
data can be clean.
Yeah. Absolutely. Pretty same for you. What what
have you observed? What what's working for you?
So we we're doing a couple of different
things, and I talked about one of them.
So we're really taking all of the information
that we're getting from providers and using a
third party company,
that looks externally at different, sources of information
when using AI and ML
to really validate all the information we're getting.
So they look at credentialing systems and other,
CMS and other, areas to say, hey. This
information is accurate or not accurate, making sure
that flow is going,
through. We also took a look at our
provider directory and how it was structured on
the back end over the last couple of
years and
have completely untangled or unraveled it and then
reorganized
it into a cloud infrastructure,
which actually just went live today.
So we're super excited about that. And what
that helps us do is, one, it drives
better quality of how all of those all
of that provider data is connected to our
plan and network data, but it also drives
accessibility
of that information across a lot of different
channels.
So customers can engage with it through a
chat,
through an agent, through a voice channel, or
through the search tool that we have today.
Yeah. It's it's constantly advancing, it sounds like.
It's you're evaluating
constantly, which is which is awesome.
Yes. Exactly. That's right.
Yeah.
You both talked about the importance of sort
of this accuracy piece. Right, Joey? You talked
about the fact that, hey. We need to
know if that provider's address in Pittsburgh is
still correct. That needs to line up. So
that's a simple
that's the simple accuracy piece. Obviously, that's what
provided data does in itself.
Can you talk a little bit about why
it's also so important
to leverage when it comes to sort of
the more overarching
theme of improving
care coordination
and then in turn really improving
the patient and member experiences.
We talk about trust, etcetera. Why is it
so important from an overarching perspective
as well, not just the accuracy piece that
we already touched on?
Yeah. Sure. I mean, I think for, like,
Preeti sort of talked about it earlier too,
but, a big strategy of ours as an
organization is called the living health strategy and
something we're working towards in the payer and
the provider systems. And, ultimately, a big part
of that is how do we
reduce, you know, stress or frustration or fragmented
approaches for our members and patients and make
it feel seamless. And I think this is
a huge part to it. You know, when
we can have this
accurate info that's integrated seamlessly
into the member portal that Preeti talked about
to
know what's up to date and they can
make their appointment more easier, that that really
reduce that fragmentation. And it strategically helps
our patients trust us and then continue to
want to come back and, and to come
to our facilities.
I think the other thing we're really thinking
about is, you know, once this
info now if you have all this
centralized about your locations and your clinicians, how
do we
redesign the way that a patient could come
to our facility? Not traditionally, I was find
a doctor. Now let's say,
make it find care truly. You know, you
should you now have all your locations info
and your provider info. You know, a patient
or member could search for my right knee
pain hurts.
What do I need to do? And we
should know that that means, you know, orthopedic.
You live here as your ZIP code, here's
the nearest facility with an open appointment. It
allows for us to get to that true
fine care experience faster. So that's something, you
know, in the future, we're really excited about
designing and building. We have all this, you
know, data accuracy upfront, in there.
Yeah. Priti, you you touched on the the
strategic lever that this can be, right, and
sort of the the initiatives too that that
you're working on to improve this. What does
this look like for you, and and how
is it streamlining that care coordination piece too?
Yeah. And I think, you know, we've been
using the word trust a lot, and we
know that all of the provider data being
accurate,
that's bad data is just gonna erode people's
trust. And when there's good data, it builds
that trust. So that's obviously core to everything
we're doing. And then on top of that,
we're layering in additional information to make sure
that when in the moment that they're actually
looking for a provider,
how do we give them information that they
need to complete that task or journey? So
how do we provide information about appointment availability?
How do we make that more personalized
with care gap information as well and make
sure that they get the right information in
those moments?
We could suggest preventative screenings.
We can also provide information
if they don't have a, let's say, physical
therapist within a 30 mile radius, how do
we connect them to our virtual physical therapy
services
and make sure that they get access to
the care that they need regardless of where
they're located or their ability to kind of
physically go into a location?
And then the other piece of that is
also to make sure that we're connecting them
with information that they want to know about
these clinicians.
In some cases, they wanna have more personal
connections if it's a primary care doctor. And
we learned this a lot through our research
that people are interested in understanding, you know,
they speak their language, can they relate to
this person? Do they offer virtual care options?
And so we wanna make sure we provide
that enhanced
provider information beyond just location,
and how to contact them so that they
can make that decision in that moment and
don't have to do additional research on third
party sites to,
get the full picture that they need to
make a decision and move forward with their
health care. That extra Googling takes a lot
of time. So I agree that this does
really improve the patient experience.
Exactly. And I'll say they've we've in our
research, we saw they were using Google, Yelp,
Nextdoor,
everything they could to kind of find that
information.
Yeah. Absolutely. I wanna close this out with
sort of a a little bit of a
forward looking view on this. Right? So we've
touched on what you all are doing, how
it's working, and sort of the initiatives that
you're you're trying to move forward in the
next couple of years or even immediately right
now.
When we are doing this correctly
and everything that we've mentioned so far,
how does that accurate provided data then also
set sort of the foundation
for
AI initiatives and other initiatives in your organization,
and what should we consider as the prerequisites
for success there? Joey, we'll start with you.
Sure. Yeah. Thanks. I talked about it briefly,
I think, on the last topic there. But,
ultimately,
if you have the information about a provider
and the location and all this data about
them, you can feed that information into,
in the future, your AI agents for call
center, your chatbot experience, and website or member
portals. And a patient or a member could
ask any question or they could say, if
I may, doctor Joey, where he practices, and
if we have all that feeding it, they
can respond quickly and then also surface when
that appointment's available with them. And so if
you have a infrastructure or base of all
that connected from the various parts of the
enterprise,
with the phone numbers, fax numbers of a
facility,
again, that clinician specialty where they work and
their schedule availability, you can then truly
enhance the next layer of engagement for our
patients and members wherever that may be in
the future. So you need that base layer,
though, to enable that experience. I mean, I
know Preeti is leading a great initiative across
our enterprise, or our call center that can
also help feed into that. Yeah. Brutee, feel
free to elaborate on that. Yeah. And I
think, you know, what Joe is referring to
is we're really trying to shift the model
in our contact centers from assistant service to
self-service.
We know that's much more efficient for members,
and then they can use a twenty four
seven support model. So if they're laying in
bed at 11:00 at night and need to
find a doctor, they don't need our contact
center to be open if we establish the
right self-service capabilities.
And the other place we're trying to start
thinking about the AI
utilization outside of just the conversational AI and,
you know, virtual,
assistance
is also personalization.
So if somebody has a care gap, how
do we connect them to the right clinician
and look at, hey. You have five clinicians
in your area. We see that you're not
attributed to a PCP, and these five have
appointments available within the next thirty to sixty
days, whatever the acceptable threshold is for that
service type,
and make those recommendations
proactively.
If we have a provider or a clinician
that leaves our network and they need to
find a new doctor that's in network, how
do we proactively
engage them and let them know that instead
of saying, hey. Your doctor is no longer
in network. You need to go find another
one. How do we actually just use AI
to make a recommendation
on some new doctors based on what we
knew about their previous physician,
and also, you know, where they live, what
their preferences are for virtual versus in person,
and then make recommendations based on that. So
we really wanna start utilizing,
AI to drive those intelligent provider recommendations,
and also driving more self-service capabilities so our
members can serve,
through any channel they want and when they
want.
Yeah. And I love that at the end
of the day, this always comes back to
improving the patient and member experiences
across the board, whether that be through, again,
improving trust or just streamlining this whole process,
which is a fantastic goal to have. Joy
and Priti, thanks so much for your time
and insights today. This was a fantastic conversation.
Thanks for being here.
Thanks so much for having us. Having us.
It was great. Yeah. Absolutely. And we also
want to thank our podcast sponsor, Kairos Health.
You can tune in to more podcasts from
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