Hello and welcome to the Becker's Healthcare podcast.
My name is Chanel Banger and I'm recording
live at the Becker's Healthcare future of dentistry
roundtable,
sitting down with Rob Giordina and doctor Ellen
Polsky. And today we're gonna discuss physio 360
and AI in dentistry.
But before we get into that, could I
please have you both introduce yourselves? Doctor Polsky,
I'll start with you.
Yes. Hi, Ellen Polsky. I am a CEO
of, one of the DSOs. We have about
30 locations,
across the country.
And I'm by training a pediatric dentist,
and this is basically the background.
Thank you. And Rob? Hi. I'm Rob Giordino.
Thanks for having us. I'm a technologist,
about 30 years of,
experience in in the data and software industry.
Couple big companies like like Amazon and Oracle,
most recently, Palantir, and now,
4 years working on our new technology, which
I'm excited to talk about today.
Well, definitely. Let's get right into it then.
Could you tell us a bit more about
how this AI relates to dentistry?
Right. So it's interesting to talk about which
kind of AI we're gonna talk about first.
So what we're talking about today is not
so much the traditional health care AI for
focusing on diagnosis. So we're not talking about
examining image imagery or trying to come to
a complicated diagnosis.
That's an interesting problem and really valuable, but
we all know that that's a work in
progress.
So, so we're, we're actually talking about the
other AI. So what we wanna talk
about today is the revolution inspired by Chat
GPT and how that relates to the dental
world.
Amazing. I'm excited to dig into this with
you both. Now, can you tell me the
challenges associated with bringing this technology into the
industry?
Well, usually, what we experience
in the dental field or any health care
field,
document to document solutions already exist, meaning we
can put some kind of document into ChargeGDP,
and ChargeGDP can analyze it.
However, in health care, we do use,
very different types of solution, business
applications,
operational
type of applications.
So the data is very complicated
and not in a document form.
So that presents significant challenge
in terms of data sorting and data organization.
Got it. And when you talk about this
data, do you mean like EHR data, prescriptions?
What all does this incorporate exactly?
Yeah. So the vision there is you really
wanna ask any kind of question. No matter
what system part of the answer might live
in, you wanna ask a question that covers
things like,
electronic health records or medical records or practice
management system. And it might involve some of
the staff. So you have an HR system.
It might involve calls or accounting, and you
really don't want to see those boundaries when
you're asking the question, and you want an
answer that can pull data from all of
them. Absolutely.
And can you walk us through how this
AI does the work for you? Okay. So
when you have all these disconnected systems, you're
really asking a little bit of your questions
out of each one. So you have to
you have to check with your accounting system.
You have to go into your patient management
system. So the idea here is that if
you pull them all together in one model
that makes sense to the business, things that
are obviously the way you would draw them
on a whiteboard, for example.
This is easy for you to combine all
your systems into that model, particularly with today's
AI. But it is also extremely
understandable.
That kind of whiteboard model is the kind
of thing that an AI, a chat gbt
style AI
can answer natural questions about.
Love to hear it. And doctor Polsky, could
you talk about exactly what you're doing today
with this technology?
Today, we're trying to set an interconnected system,
and one of the aspects that we used
to struggle with that manual
is absolutely terrible and horrible.
Any type of reports that any of my
staff members were trying to pull out manually
was requiring a lot of labor.
And that part, I think this particular technology
can solve very beautifully and elegantly for us.
So in many situations when the company tries
to pull out the data manually,
you end up in a scenario where you're
acting very reactively.
Somebody urgently needs the data. They pull all
the resources. They try to put 5 people
or 10 people on a task and pull
that data manually, and then they kind of
go and forget it. So what this solution
does, it
crisply
defines that particular problem as
I can ask any questions for my data,
and now no manual resources are necessary
to answer the questions all across the system.
Got it. And that brings me to my
next question. How do you put this all
together, and what is your new vision with
this?
Okay. Sure. So that's a big question because
we're we're changing that future. We're evolving it
now. But I think we can go back
to what everybody really wants about their practice.
They really
like, the best decision that you can make
about a difficult issue is when you have
the perfect spreadsheet in front of you. All
the exact right numbers, nothing
irrelevant, just so that you can understand a
pattern or make a make the best possible
decision. So that's where we're going. We wanna
always be able to have and assemble just
the right amount of data for us for
for today, which requires that, as we talked
about earlier, you have to be able to
interconnect all your data. It can't be unavailable
just because a little bit of the data
is in a different system. So you also
want that to be automated so that it's
always working for you on a clock and
always up to date.
And clearly, as Ellen said, you just wanna
be able to answer any question, any reasonable
question. You know what's in the data. You
just wanna be able to answer it fluidly
as your needs change day by day. Thank
you so much for walking us through that.
And I'll turn it back to you, doctor
Polsky. What value would you say this brings
to the customer?
Well, the biggest value it brings, my CEO
used to
spend about 2 hours daily trying to pull
the reports together from various data sources to
combine into 1 Excel spreadsheet
and also occupying valuable resources for that particular
task. So reduction in labor cost is absolutely
one of the biggest valuable parts that we
see. Secondly,
since the data is so interconnected,
we actually can trace the patient outcomes, which
in medicine, we are starting to see in
the solutions. In terms of dental, we don't.
So
patient outcomes
are improving because of this type of data
pools. And thirdly,
we are able to react proactively
towards the problems, not being in constant reactive
mode, which is less stress on my employees,
much more relaxed environment,
and now we're planning ahead versus constantly reacting.
So we kind of all know the best
algorithms for running our practices,
but we just don't have that cohesive data
layer to deploy it. So I think let's
kind of get together and start doing it.
Got it. I love the interoperability of all
this. Well, Rob and doctor Polsky, I wanna
thank you for your time today. But before
I let you go, is there anything else
that listeners should know?
I think Ellen said it really well, and
that's the final word, is that everybody knows
the algorithms they wanna use to optimize their
business. The data stands in the way, and
it shouldn't. You should get to a place
where you have it fully connected and you
can put your best ideas into practice.
Love to hear it. Well, doctor Polsky and
Rob, I wanna thank you once again for
your time today and for sharing your insights
on the Becker's Healthcare podcast. Thank you. It's
great to be here. Thank you.