April 10, 2025 • 35 mins
"The idea is you could use AI and technology to help understand this data such that we can quantify it much more so, so that it can lead to much more objective decisioning rather than subjective decisioning,” Founder and CEO Wardah Inam explains to Bloomberg Intelligence. In this Vanguards of Health Care podcast episode, Inam sits down with BI analyst Matt Henriksson for an in-depth interview to talk about Overjet, how its AI platform can analyze digital imaging that are already in the markets to make an tangible dental decision, and how Review Pass can connect directly with the insurers to reduce the coverage decision process from weeks to minutes.
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Episode Transcript
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Speaker 1 (00:16):
Welcome to another episode of the Vanguards of Healthcare series.
My name is Matt Hendrickson, the medical technology analyst at
Bloomberg Intelligence, which is the in house equity research platform
of Bloomberg ELP. We're pleased to have with us today
WARDA and m CEO of Overjet, a privately held medical
device company that is applying artificial intelligence for a holistic
(00:37):
approach to dental care and management. Warda, thank you for
joining us today.
Speaker 2 (00:41):
You for having me here.
Speaker 1 (00:43):
Absolutely and Warda, why don't we just start because your
background story for how you found an Overjet was a
rather interesting one, So why don't we just start off
with your background story of how you found the company
and you know, a quick summary for listeners new to
the name about what Overjet does.
Speaker 2 (01:00):
Overjet is an AI company focused in healthcare, particularly in dentistry.
We help analyze dental data and such that we can
computers can utilize it and not just humans dealing with
that data. So before Overjet, all this data was unstructured.
Think of extras, think of notes, think of other information
(01:22):
that dentist collects in an office. And we were able
to utilize AI to structure that information such that computers
can utilize it and help automate and then augment different workflows.
Speaker 1 (01:35):
Interesting, and then how did you get to founding this company?
Speaker 2 (01:40):
So for me, it was a personal experience where I
changed my dentist when I was in Boston and got
it a treatment plant which was very different than what
I had received before. And this was six months apart,
so it wasn't a long time, and that got me
(02:01):
interested in dental diagnosis. I asked for my extras, started
reading Dental one oh one, realized that there was a
variation here, and then got opinions from multiple other dentists
around what their thoughts were. It felt more of an
art rather than science to me. Everybody had their different opinions.
It was hard for them to explain to me what
(02:22):
was going on. And the idea was that, hey, if
you could use AI and technology to help understand this
data such that we can quantify it much more so
that you can lead to much more objective decisioning rather
than subjective decisioning. And then you know, going one step further,
can we actually then utilize that data to to visualize
(02:45):
the disease effectively on the X rays and other modalities
so that the patients understand their oral health as well
and can make the best decisions based on the evidence
that they see.
Speaker 1 (02:57):
Okay, so it sounds like the one dentist may or
may not have seeing a little chip in your tooth,
and then you go to the other dentists and then
he's like, well, I actually see that, or I don't
see what that. I don't know what he was talking about.
So I guess that's that subjectivity that you're talking about, exactly.
Speaker 2 (03:11):
And I think there's a lot of subjectivity when it
comes to cavities, which you know, people have experience many,
you know, one of the most common conditions. There's also
other issues like bone loss or pretypical radio lucencies, et cetera.
So I think there's every condition has a different variation
(03:32):
and different accuracy of diagnosis, and being able to then
help conditions be more confident in their diagnosis, make much
more effective diagnosis, and then communicate with patients more effectively
as well.
Speaker 1 (03:46):
Yeah, that's interesting. There is always kind of I almost
feel like there's a little bit of a competitiveness between
different dentists that they want to make their products or
their their skills sound better than other people's skills, which
kind of then turns into what you were talking about.
You're you know, you're talking about the transition from the
subjectivity to the objectivity and be able to say this
is actually what it is the thing that I've noticed though,
(04:10):
Or let's go back to that subjectivity, because what are
the dentists using. Is it just are they just you know,
using that little mirror to be able to find, you know,
see that little chip in the tooth? Is it just
X ray imaging? Is there a variety? I mean, how
how are the dentists before overjet and you know traditionally
kind of finding and you know, being able to diagnose
(04:33):
the patient and their teeth.
Speaker 2 (04:35):
So are very sophisticated in how they collect the data.
So I think it's even more sophisticated than how your
pec P collects the data, which is, you know, they'll
hit you, put shine light in your eyes, or hit
you on your knee and see the reflection of there.
In dentistry, there's a lot of data collected in your
(04:56):
diagnostic visit. One of the you know, you have hundreds
of data points, you have very re charting where the
hygienesis going in and probing you know, different pockets in
your teeth. There's the X rays where they're taking at
times eighteen X rays and different types of extras to
really capture that not only your teeth, but the bone,
(05:18):
the gut and other infections that might be existing there.
Then you have your guns and other things being analyzed
either visually or through or imaging, so you know, you
have cameras that are being utilized. There's also now scans,
three D modeling and scans being utilized, so that there's
actually a significant amount of digital data that gets collected. However,
(05:40):
it was never really utilized effectively by computers, and the
only the way then this were diagnosing or creating frequent
plans was by looking at it by eyeballing distances and measurements.
There weren't tools really measuring things on these on this
data as well. So for example, but one of the
(06:01):
important measurements is how much do how much is their
bone loss? And that you do it do that you
measure based on every tooth and you're talking about sixty.
Speaker 3 (06:11):
Four measurements that you need to do.
Speaker 2 (06:14):
Very unlikely that somebody does it, you know, manually, sixty
four times on somebody's mouth. So having technology and automated
tools that help you measure that then bring that information
front rather than either your eyeballing or taking you know,
forever to measure can really help in getting too much
more objective decisioning.
Speaker 1 (06:34):
Yeah, no, that makes sense because it's just the same
as you know, what we're seeing throughout the rest of
AI is that you have all this data, how can
the computers and how can the software be able to
streamline it to a simplified and objective answer. But it's
not just the dentist as well, and I know we're
going to dive into this a little bit more, but
there's also the DSO component and the insurance companies that
(06:58):
could benefit from kind of stream lining all this data.
So why don't we start first just a simple question,
what is a d s O and how how does
that fit into the whole dental market.
Speaker 2 (07:14):
The good thing is that a DSO is a dental
service organization. And why I said good thing is it's
just a collection of multiple offices and a managerial organization
that helps manage it. So it is you know, you're
still talking about the dental practices, You're still talking about
the care that is being delivered to the patients. And
there's not that much difference between a practice that is
(07:36):
a solo practice or if it is part of a
dental service organization. And what the fundamental reason for a
practice to affiliate with the dental service organization is that
the DSO can bring a lot of economies of scale.
So if you have a hundred practices, you can negotiate
better on pricing, you can negotiate better on reimbursements, you
(07:57):
can you know, help in marketing better, you can collecting
much more effectively. So it actually is a collection of
a group of organization or a group of practices coming
together under a manager organization.
Speaker 3 (08:11):
Uh.
Speaker 2 (08:11):
And the manager organization might be backed by private equity
or might not be a lot of the data service
organizations are backed by private equity, so they have deeper
pockets and being able to then acquire more practices and
think a little bit more longer term.
Speaker 1 (08:27):
Okay, So it's basically when you're talking about the economy
of scales, they have one admin team that can really
process all the claims and then get those claims over
to the insurance companies in order to get paid. That's
kind of the like one of the key benefits of
having a DSL and that matter.
Speaker 3 (08:42):
That's one.
Speaker 2 (08:43):
That's one, But I would say a lot of it
has to all to do with the marketing, right, So
like putting marketing under one umbrella, having you know, being
able to acquire customers in any region and being able
to like then share share those patients across the different practices.
Visual to staffing is a big problem for dental practices
of being able to like staff get get the right staffing.
(09:05):
There's like all this administrative overhead that a practice has
to deal with beyond just claims that a dental service
organization can help provide.
Speaker 1 (09:15):
Okay, And then turning to then the insurance companies themselves.
I mean they're getting all these claims and basically how
do they most efficiently go through those claims and say, Okay,
this one can get paid, this one was probably unnecessary.
Speaker 2 (09:33):
Is it just.
Speaker 1 (09:33):
Manual claim by claim or do they have a you
know kind of traditionally a pattern of being able to
filter out good claim from bad claims.
Speaker 2 (09:44):
So insurance companies have technology systems, so they have their
own systems that they receive data and here it might
be digitally received, it might be you know, payper copy
that they're scanning in and putting into the system. So
claim could come in different forms, and it does come
(10:04):
in very different forms. That means quality of data becomes
a problem. However, after that, what happens is that there
is based on the rules determined. You know, it could
be your frequency, it could be limitations on your plan,
it could be many different things, and claims might fall
(10:24):
in different buckets based on that piece of it. And
then after that you have a decision around, hey, here
are the claims we want to review. Here are the
claims we don't want to review. Prior to overjet, the
review claims were all being touched manually. That means if
a claim had to be accepted, it was still going
through a manual review and resulting in a lot of
(10:45):
cost as well as inaccuracies. So like two reviewers were
disagreeing with each other, they didn't have the right tools
to make that review as possible as well. Sometimes you
were logging to ten or three different systems to get
the data for a patient. You might collect the wrong
data from a single another patient and you know, be
(11:06):
looking at it because everything was being done manually. You
were copy pasting image links with the patient links. There
was no single system where it was just collecting all
the data bringing it to towards the dentists and having
and I say dentists because on the review side, it's
also dentists that are involved and being able to provide
(11:26):
them that information.
Speaker 3 (11:27):
And then all the claims that were getting accepted.
Speaker 2 (11:30):
Or request needed requests from more information, they were still
going through this review. That means weeks were being spent
before decision was being made.
Speaker 3 (11:37):
And by being able to say, hey, here are the claims.
Speaker 2 (11:39):
That are like that can just be accepted, let's just
pay these out. Let's uh or after more information quickly
so that you know, people can provide the information as well.
And then here are the claims that might lead to
an adverse decision. Let's let's review those, but let's review
them thoroughly, uh a bit fast, you know, so you
don't want to spend forever on reviewing claim because that
(12:01):
cost can be that high because you know, again the
and the end the members are paying for it, right,
so the you know, the cost needs to be lower
and it needs to be consistent as well, So two reviewers,
you should come to the right solution. So the if
treatments needed should get paid if it meets the plant
guidelines should get paid and what does that need to
(12:21):
look like? And that's that was the contribution of overjet.
Speaker 1 (12:25):
Yeah, so let's just jump right in. I mean it
sounds like, with you know, the current market environment, it
sounds like you need to have a system that can
consolidate multiple other systems into one kind of cohesive platform.
So how does your platform work? How does overjet be
(12:47):
able to get all that information from the X rays
all the way to the insurance claims and being able
to go through that process into that one platform.
Speaker 2 (12:57):
Yeah, so we actually just hook into everything that that exists,
into the systems where they're scanning the paper dogs, into
the systems you know, my re clearing houses that they're
getting the information from. It might be their own internal
systems that they're connecting with. So being able to connect
with all the different systems that exist and being able
(13:17):
to then understand what the data is so you know,
where we can say, hey, this is a photograph, this
is an xt rate, this is a document, and that
helps saying okay, what do we need to do with
that information and where does it need to fit in.
And it doesn't come as a blob of data for
a reviewers, while it falls into like nicely designed templates
so that people can know, here, here's my photographs, here's
(13:39):
not you know, with the information is and be able
to then have claims return faster and then reduce reduced
costan make much more accurate decisions because there is a
pass of you know, it goes through and through this analysis.
Speaker 1 (13:56):
Okay, and so then I mean, so it's being able
to you know, high level be able to you know,
distinguish what's a photo, what's an X ray, and then
kind of what's a document and then I'm assuming within
that document then they can kind of say what is
a certain claim for you know, a cavity being filled
versus what's a claim for a root canal? And then
(14:17):
goes kind of even going further that because I'm assuming
these d s O s and these insurance companies they
have subtly different language for what can be covered and
what can't be covered. So how does the system be
able to be able to understand that subtlety?
Speaker 2 (14:37):
I would say that the organizations utilies in the software
configure the software for their needs. So you know, overget
is on deciding a claim whether it should fall here,
or for should fall in this bucket or that bucket, et, cetera.
It's a very configurable platform that allows for pairs to
be able to configure their plans. And it's actually very
(15:01):
interesting where you know, for example, in medicaids, you have
you have fifty different states. You might have fifty different
rules for for a single procedure. So you talk about hundreds,
if not thousands, of different rule sets that a company
is actually managing in their systems, and and and then
applying those rules based on what the uh, you know,
(15:23):
what state that claim is coming from, what plan the
patient is on UH, and many other checks which end
up determining different rules and edits okay.
Speaker 1 (15:35):
And so that's kind of on the payer side. Let's
let's kind of circle back to you know, the dentist,
the you know, the kind of the front line there
with the patient. You have you have these x rays.
What is Overjet providing in the analysis of those x
rays to kind of make it that objective decision on
if there is a cavity there or if it's just
(15:55):
you know, something else, or if it's worse than a cavity.
Being able to make those kind of you know, we're
talking about multiple dentists having multiple opinions about the same tooth.
How do we make that into that one decision?
Speaker 2 (16:08):
Yeah, So I think the interesting thing is, you know
why you could have multiple opinions is mostly around the
treatments as well. So you could have a cavity, but
you could do a filling, you could do a crown,
you could could do a root canal, you could do
a bridge, you could extract the two. There's like so
many things that you could do with it based on
the cavity. And the reason you might do one thing
(16:28):
or the other might depend on the structure of the tooth.
It might depend on the bone levels, it might depend
on how you know past history, you are there any restorations.
Speaker 3 (16:38):
On that tooth, et cetera.
Speaker 2 (16:40):
So being able to take take all that data in
and being able to say, okay, here's where you know
where the cavity is, here's outlining that out and sync
and how it interacts with the rest of the anatomical structure,
as well as if there are other restorations, et cetera.
Speaker 3 (16:55):
Coming to.
Speaker 2 (16:57):
And then utilizing guidelines to be able to say, okay,
if that's you know, if it is close to the
pulp you might need a root canal for example, and
how much to the pulp. You know, that's one where
you know there might be some variations that occur, but
once you can agree on what the guidelines are, you
can actually come to a very objective decision. So being
(17:17):
and and the way it manifests itself is it think
of it as if you've seen an extray. I think
of it as an outline that's outlining how much that
X ray is it's actually collecting, uh is, calculating.
Speaker 3 (17:29):
Ratios of that tooth.
Speaker 2 (17:30):
Area with how much the crown area of your tooth
is uh so cavity over the tooth area of the crown,
and being able to determine what the right treatment there
would be based on whether there's a pass restoration or
other conditions they are present.
Speaker 1 (17:48):
Okay, And so I mean, I guess when I'm thinking
of AI, you kind of have historical data of other
teeth and they've been labeled as a cavity or the
root canal or something like that, and then that gets
incorporated into the current image. Is that kind of the
machine learning that's taking place with the diagnostic portion of overjet.
Speaker 2 (18:07):
Yeah, So the interesting thing is the air part goes
on a lot of paid places. So the first is
what you call it image enhancement. So as images come
in and saying in dental practice, the quality of that
image might vary, might have been overexposed with radiation, there
might be less, they might be very bright and by
different contrasts.
Speaker 3 (18:28):
There you know, and there might be other just the
type of sensor, et cetera.
Speaker 2 (18:34):
So being able to enhance the image which in a
way that standardizes it based on the contrast and all
this other brightness and other pieces that need to be defined,
and we are FT cleared for that. That that AI
models are FDA cleared and very sophisticated in how they
enhance those images without impacting the clinical findings, so the
(18:54):
findings remain intact and it's able to remove the noise
from the image effectively. Then you have AI finding the
findings the clinical findings, then AI finding anatomical structures UH
and being able to identify those so it goes in
like different and then then you know you're doing all
the way from like key points to segmentations to detections
(19:18):
and other models that run to determine what type of
extra it is you know what you know and and
and so that you can run the very specific models
because we're trying to get to higher and higer accuracies
and and and surpass then just level accracies. And so
there's classification, detection, segmentation, you know, key points, all these
(19:40):
other models run that that get to the outputs.
Speaker 1 (19:43):
Oh interesting, And then you know we're talking about you know,
turning back to the payers again. It kind of all
circles back in with you being able to help with
the faster decision making for insurance claims. You also just
recently launched a new system called review Pass. So what
is review Pass and how does that help the whole
(20:04):
process even expedite or how does it expedite the process
even quicker.
Speaker 2 (20:10):
So I think review Pass is a game changer in
the industry. And what it does is it gives an
ability to the provider, with the click of the button,
be able to skip the manual insurance review. And that
is so beneficial for the patient for example, because rather
than waiting thirty days and getting a surprise bill at
the end, they are getting a decision within less than
(20:32):
a minute, and that gives them a lot of confidence
in what treatments that are being recommended by the dentists,
how insurance will will reimburse them, and how much they
will have to pay out of pocket, because again, having
this surprise bill of one thousand dollars is for a
crown for example, is very hard for many Americans to
(20:55):
be able to pay for. And by being able to
have that information right there, knowing an s in it
around what insurance book is very important. So review pass
is very important for that. But it's also helpful for
providers because they spend a lot of time trying to
get eligibility and benefits of information, trying to get information
from the provider around the treatment that needs to happen.
(21:18):
By being able to then have that data just being
present within in less than a minute with the press
of a button, stops them from calling forty five minutes
into a dental office and collecting this information and it's
right there as well as for the insurance companies because
you know, if providers are calling, payers are listening or
(21:38):
and talking back as well, so you're spending forty five
minutes there as well sharing of information of that patient.
And how do we actually make that seamless? So and
I think it also leads to having everybody more aligned
and having more trust in the system as well.
Speaker 1 (21:55):
Yeah. No, absolutely, especially when you kind of have that
comfort level that the decision you're going to make is
going to actually go through the insurance claims properly. Now,
this sounds like the other end of the spectrum that
we just kind of talked about a few minutes ago
about all the previous X rays that have been analyzed
as kind of the data the input values for the
(22:16):
new output, which is the current patient. This is going
the other way where it's are you reviewing hundreds and
thousands and thousands of previous insurance claims and seeing which
procedures got covered by particular insurance companies and then kind
of going through that process of evaluating whether or not
(22:37):
there's a probability that that would be covered for a
future procedure.
Speaker 2 (22:41):
No, here, we're actually connecting directly with the BEAR system
and getting a response back in real time. So this
isn't you know, us guessing. This is us bringing the
BEAR system, getting a response back, and being able to
then display that response to the provider. And in order
to be able to do it, we had to work
(23:03):
with the pairs to have their systems be real time
there you know, every everyone had batch processing, everyone had
you know, uh, this process is a week multiple week
long process. That we were able to shrink it down
to less than a minute and be able to bring
that to life. So it is you know, pretty fascinating
(23:25):
to see how how pairs were able to make that
happen and how providers were able to help them to
make that happen as well.
Speaker 1 (23:33):
Oh that is interesting, Yeah, because I was assuming that
you guys were making the best guess based off of
all the data yet, but this is now you're already
communicating with the payers at this point already.
Speaker 2 (23:44):
And that's what the future should be, right Like you know,
in today's day and age, why should we submit things
which you know, mail things in and wait for things
to come back like we have digital communication and and
APIs that can talk back and forth. There's a lot
of infrastructure to be built in to be able to
do this effectively, but you know that's where and to
enable the yeah, to make this happen. But you know,
(24:07):
I think there is appetite on both sides to do so.
Speaker 1 (24:10):
Yeah, no, absolutely, I agree with that. And so this
kind of was going to roll into my next kind
of set of questions about kind of the commercial rollout
of Overjet. But I'm going to just start continuing with
this payers, you know, the the review pass, because you
already need to have a relationship with some of these payers,
they already need to be on board. So kind of
(24:32):
what percentage of covered lives you know, do you already
have covered under this review pass with having you know,
payers be on board already?
Speaker 2 (24:42):
Yeah, so so Overjet serves majority of the top insurance
companies representing about one hundred and thirteen million lives. For
the review pass we have about this is you know,
again brand new, first time ever being introduced as and
pairs basically saying we're in for the ride and taking
(25:04):
a risk on us and taking a risk on and
having faith in in dentists to do the right thing
and exposing these systems and making sure that in the
end the members actually benefit for that. We have pairers
represent about forty million members and these are pairs like MetLife, Humana, Guardian,
(25:26):
et cetera, who are saying, hey, we are going to
be at the forefront of this UH and spend resources
to make sure that we are providing better service to
our members and improve the provider pair friction that exists.
And then we have provider groups as well taking part
(25:46):
in making this happen because we want to do it
at scale to start off with. So you have companies
like Dental Care Lines, Interdent, North American Dental, Smileless, Core Dental,
et cetera. We're saying, hey, we were going to participate
in this as well and figure out all the kings
and figure out all the areas and really start to say, hey,
what's how do you work on more experience as well
(26:09):
and really build us out. You know, this is I believe,
the first step, and there's many more steps to be
had here.
Speaker 3 (26:17):
Yeah.
Speaker 1 (26:17):
No, and that's all interesting. What got my attention though,
is well, we talked about previously about how the antiquated
way of you know, insurance companies covering claims and you
would have to have sometimes two people in the in
the company kind of reviewing the same claim because you
want some you know, the balance the quality and the
speed and everything. But this sounds like by you know,
(26:39):
having the review passed and having it kind of already
you know, it takes one minute to kind of get
that approval and you don't need those two employees anymore
wasting their time doing one claim. They can go and
do other things to help out with the insurance companies
and other various aspects of the efficiency of pain out
for these patients. And so then you're talking about the
(27:01):
dental companies, the DSOs as well getting on board. I mean,
how long has Overjet been out in the market at
this point.
Speaker 2 (27:10):
So we started the company started in twenty eighteen, so
August twenty eighteen, so been it's been a while here.
We started selling to dental practices in We got our
first of declarance in twenty twenty one and really started
rolling this out in twenty twenty two.
Speaker 1 (27:27):
Okay, So how has that rollout over the last two
two and a half years, Ben? And how has that
built the foundation now for this review pass as you
kind of get that launched off the ground.
Speaker 2 (27:39):
I think for us now we serve nine out of
the top fifteen dental service organizations with the larger groups there,
we also serve a lot of you know, solar practices,
thousands of solar practices as well, and as we roll
out review Pass, we are also partnering with other companies,
(28:01):
other practice manishment systems who are just distributing this across
their member base as well. So, so it is you know,
utilizing that customer base we have and then customer base
of our partners to be able to launch this across
the United States.
Speaker 1 (28:20):
Yeah, and then so and then how how is the
commercial team built out to be able to expand that?
Is this something there you have to have sales reps
knocking on door to door at each dentist office, then
going to the insurance companies or is there a new
way of being able to have this kind of outreach?
Speaker 2 (28:39):
Yeah? So I think with the review pathel, we're right
now offering it to our customers. So these are not
new customers yet. Uh, as we expand that further, we
will you know, I offer to other folks as too,
either sorry our customers or our partners customers. And but
(29:00):
in general, like how we get to customers is through
inbound and outbound sales, and there's a lot of you know,
people who reach out to us as well on our
website and schedule a demo and then get on board.
The good thing is most of it happens virtually, and
that helps to scale much more effectively.
Speaker 1 (29:21):
I was about to say, yeah, you don't have to
travel to each dentist in the state or the county
or anything like that. So then you know, we're talking
about review pass and I know that it just came out,
but I'm assuming that this is not it for product
development for overjets. So kind of what are some of
the next developments beyond that that you're working on to
(29:43):
make this a more holistic approach for the kind of
the dentists and for the payers.
Speaker 2 (29:48):
Yeah, so this is part of what we call the
Dental Clarity Network. So we actually introduced an inter or
cross industry collaboration around reducing the provider and bear friction
and reducing the cost in current as well. So which starts,
you know, with eligibility and benefits automation, so in short,
verification automation, review pass, claim submissions automation to reduce that
(30:14):
overhead for customers credentialing. You know, that's also a pain
point between providers and pairs. Being able to work on
these pieces which you know, which either originated on the
provide sid or originated on the pair side will cause
a lot of friction between the two and being able
to solve them through technology and partners who are really
(30:35):
committed to a better member and provider experience.
Speaker 1 (30:39):
Yeah. No, that kind of goes back to that whole,
you know theme that we're talking about through us an
entire half hour so far has been just subjectivity versus objectivity.
And if you have two people budding over how much
that you want to pay or if they're going to
pay for it, if you gain all that data to
be able to say, hey, this is actually what it is,
this is what it has been historically paid for, you
don't have to worry about that butting of heads anymore.
(31:00):
And so we're kind of going then back to the
review pass. I mean, we're just launching it here in
March of twenty twenty five. When you come back onto
this show in March of twenty twenty six, what how
do you how do you see that ramping up in
that kind of twelve month time frame.
Speaker 2 (31:22):
So I really do think that in a year or
so we can completely eliminate what it's called ROUNDEUS cycle management,
and that is, you know, this idea of introance verification
and claim submission and eobs and like dealing with all
(31:42):
this paperwork and their teams like there are hundreds of
people in these organizations dealing with that information, and can
we actually have that these this administrative work be automated
and can we have this so it says that there
is reduction costs as well as accuracy in these systems.
(32:03):
I think that's very possible in the next year and
be able to then, you know, hopefully utilize these folks
towards you know, you want them communicating with patients. You
want them helping patients get the best care, not dealing
with paperwork. And how do we make that happen?
Speaker 1 (32:23):
Yeah, and you know what, I would love to see
that happen down the road because yeah, just you know,
from my experiences too, not knowing what exactly you're gonna
have to pay for until you kind of put out
your credit card for the out of pocket payment. Definitely
would like to have that more information like that in
the future, you know. As we close up, though, you know,
it's a great story about how you came to found Overjet.
(32:47):
One of the things I like to ask guests on
the show is you know, was there a specific book
or group of books that you've read over your time
at school or recently that's helped you be able to
drive over Jet to where it is today.
Speaker 2 (33:06):
I would say I constantly read books which help in
building of the company and uh uh and managing off
the off the people, et cetera, and and different scale
of the company. There's different books that come into play.
I think one of them which has been very instrumental
UH is a clear use scaling people really around you know,
(33:30):
how do you manage much more effectively in build systems
around it? I think, UH, there's a book on Amazon
working backwards has been very useful as well. I recently
read a book Sales Acceleration Formula around how do you
scale up the teams, which is I think really helpful
for growth. So I think at different stages, you know,
(33:50):
different books have helped in shaping how Overjet has uh
has evolved, as well as how I view company building.
Speaker 1 (34:00):
Nice and I think that's a nice little spring break
reading while you're at the beach and everything. Yes, but Wada,
thank you so much for joining us today. This was
a very thoughtful conversation we had today.
Speaker 2 (34:12):
Oh, thank you, Matt, thank you so much for having me.
Speaker 1 (34:15):
And thank you to our listeners for tuning in today,
and we hope you join us for future episodes. If
you would like to stay up to date, you can
click the subscribe button on Spotify or your favorite streaming platform.
Take care
Speaker 2 (35:01):
Lass
Welcome to another episode of the Vanguards of Healthcare series.
My name is Matt Hendrickson, the medical technology analyst at
Bloomberg Intelligence, which is the in house equity research platform
of Bloomberg ELP. We're pleased to have with us today
WARDA and m CEO of Overjet, a privately held medical
device company that is applying artificial intelligence for a holistic
(00:37):
approach to dental care and management. Warda, thank you for
joining us today.
Speaker 2 (00:41):
You for having me here.
Speaker 1 (00:43):
Absolutely and Warda, why don't we just start because your
background story for how you found an Overjet was a
rather interesting one, So why don't we just start off
with your background story of how you found the company
and you know, a quick summary for listeners new to
the name about what Overjet does.
Speaker 2 (01:00):
Overjet is an AI company focused in healthcare, particularly in dentistry.
We help analyze dental data and such that we can
computers can utilize it and not just humans dealing with
that data. So before Overjet, all this data was unstructured.
Think of extras, think of notes, think of other information
(01:22):
that dentist collects in an office. And we were able
to utilize AI to structure that information such that computers
can utilize it and help automate and then augment different workflows.
Speaker 1 (01:35):
Interesting, and then how did you get to founding this company?
Speaker 2 (01:40):
So for me, it was a personal experience where I
changed my dentist when I was in Boston and got
it a treatment plant which was very different than what
I had received before. And this was six months apart,
so it wasn't a long time, and that got me
(02:01):
interested in dental diagnosis. I asked for my extras, started
reading Dental one oh one, realized that there was a
variation here, and then got opinions from multiple other dentists
around what their thoughts were. It felt more of an
art rather than science to me. Everybody had their different opinions.
It was hard for them to explain to me what
(02:22):
was going on. And the idea was that, hey, if
you could use AI and technology to help understand this
data such that we can quantify it much more so
that you can lead to much more objective decisioning rather
than subjective decisioning. And then you know, going one step further,
can we actually then utilize that data to to visualize
(02:45):
the disease effectively on the X rays and other modalities
so that the patients understand their oral health as well
and can make the best decisions based on the evidence
that they see.
Speaker 1 (02:57):
Okay, so it sounds like the one dentist may or
may not have seeing a little chip in your tooth,
and then you go to the other dentists and then
he's like, well, I actually see that, or I don't
see what that. I don't know what he was talking about.
So I guess that's that subjectivity that you're talking about, exactly.
Speaker 2 (03:11):
And I think there's a lot of subjectivity when it
comes to cavities, which you know, people have experience many,
you know, one of the most common conditions. There's also
other issues like bone loss or pretypical radio lucencies, et cetera.
So I think there's every condition has a different variation
(03:32):
and different accuracy of diagnosis, and being able to then
help conditions be more confident in their diagnosis, make much
more effective diagnosis, and then communicate with patients more effectively
as well.
Speaker 1 (03:46):
Yeah, that's interesting. There is always kind of I almost
feel like there's a little bit of a competitiveness between
different dentists that they want to make their products or
their their skills sound better than other people's skills, which
kind of then turns into what you were talking about.
You're you know, you're talking about the transition from the
subjectivity to the objectivity and be able to say this
is actually what it is the thing that I've noticed though,
(04:10):
Or let's go back to that subjectivity, because what are
the dentists using. Is it just are they just you know,
using that little mirror to be able to find, you know,
see that little chip in the tooth? Is it just
X ray imaging? Is there a variety? I mean, how
how are the dentists before overjet and you know traditionally
kind of finding and you know, being able to diagnose
(04:33):
the patient and their teeth.
Speaker 2 (04:35):
So are very sophisticated in how they collect the data.
So I think it's even more sophisticated than how your
pec P collects the data, which is, you know, they'll
hit you, put shine light in your eyes, or hit
you on your knee and see the reflection of there.
In dentistry, there's a lot of data collected in your
(04:56):
diagnostic visit. One of the you know, you have hundreds
of data points, you have very re charting where the
hygienesis going in and probing you know, different pockets in
your teeth. There's the X rays where they're taking at
times eighteen X rays and different types of extras to
really capture that not only your teeth, but the bone,
(05:18):
the gut and other infections that might be existing there.
Then you have your guns and other things being analyzed
either visually or through or imaging, so you know, you
have cameras that are being utilized. There's also now scans,
three D modeling and scans being utilized, so that there's
actually a significant amount of digital data that gets collected. However,
(05:40):
it was never really utilized effectively by computers, and the
only the way then this were diagnosing or creating frequent
plans was by looking at it by eyeballing distances and measurements.
There weren't tools really measuring things on these on this
data as well. So for example, but one of the
(06:01):
important measurements is how much do how much is their
bone loss? And that you do it do that you
measure based on every tooth and you're talking about sixty.
Speaker 3 (06:11):
Four measurements that you need to do.
Speaker 2 (06:14):
Very unlikely that somebody does it, you know, manually, sixty
four times on somebody's mouth. So having technology and automated
tools that help you measure that then bring that information
front rather than either your eyeballing or taking you know,
forever to measure can really help in getting too much
more objective decisioning.
Speaker 1 (06:34):
Yeah, no, that makes sense because it's just the same
as you know, what we're seeing throughout the rest of
AI is that you have all this data, how can
the computers and how can the software be able to
streamline it to a simplified and objective answer. But it's
not just the dentist as well, and I know we're
going to dive into this a little bit more, but
there's also the DSO component and the insurance companies that
(06:58):
could benefit from kind of stream lining all this data.
So why don't we start first just a simple question,
what is a d s O and how how does
that fit into the whole dental market.
Speaker 2 (07:14):
The good thing is that a DSO is a dental
service organization. And why I said good thing is it's
just a collection of multiple offices and a managerial organization
that helps manage it. So it is you know, you're
still talking about the dental practices, You're still talking about
the care that is being delivered to the patients. And
there's not that much difference between a practice that is
(07:36):
a solo practice or if it is part of a
dental service organization. And what the fundamental reason for a
practice to affiliate with the dental service organization is that
the DSO can bring a lot of economies of scale.
So if you have a hundred practices, you can negotiate
better on pricing, you can negotiate better on reimbursements, you
(07:57):
can you know, help in marketing better, you can collecting
much more effectively. So it actually is a collection of
a group of organization or a group of practices coming
together under a manager organization.
Speaker 3 (08:11):
Uh.
Speaker 2 (08:11):
And the manager organization might be backed by private equity
or might not be a lot of the data service
organizations are backed by private equity, so they have deeper
pockets and being able to then acquire more practices and
think a little bit more longer term.
Speaker 1 (08:27):
Okay, So it's basically when you're talking about the economy
of scales, they have one admin team that can really
process all the claims and then get those claims over
to the insurance companies in order to get paid. That's
kind of the like one of the key benefits of
having a DSL and that matter.
Speaker 3 (08:42):
That's one.
Speaker 2 (08:43):
That's one, But I would say a lot of it
has to all to do with the marketing, right, So
like putting marketing under one umbrella, having you know, being
able to acquire customers in any region and being able
to like then share share those patients across the different practices.
Visual to staffing is a big problem for dental practices
of being able to like staff get get the right staffing.
(09:05):
There's like all this administrative overhead that a practice has
to deal with beyond just claims that a dental service
organization can help provide.
Speaker 1 (09:15):
Okay, And then turning to then the insurance companies themselves.
I mean they're getting all these claims and basically how
do they most efficiently go through those claims and say, Okay,
this one can get paid, this one was probably unnecessary.
Speaker 2 (09:33):
Is it just.
Speaker 1 (09:33):
Manual claim by claim or do they have a you
know kind of traditionally a pattern of being able to
filter out good claim from bad claims.
Speaker 2 (09:44):
So insurance companies have technology systems, so they have their
own systems that they receive data and here it might
be digitally received, it might be you know, payper copy
that they're scanning in and putting into the system. So
claim could come in different forms, and it does come
(10:04):
in very different forms. That means quality of data becomes
a problem. However, after that, what happens is that there
is based on the rules determined. You know, it could
be your frequency, it could be limitations on your plan,
it could be many different things, and claims might fall
(10:24):
in different buckets based on that piece of it. And
then after that you have a decision around, hey, here
are the claims we want to review. Here are the
claims we don't want to review. Prior to overjet, the
review claims were all being touched manually. That means if
a claim had to be accepted, it was still going
through a manual review and resulting in a lot of
(10:45):
cost as well as inaccuracies. So like two reviewers were
disagreeing with each other, they didn't have the right tools
to make that review as possible as well. Sometimes you
were logging to ten or three different systems to get
the data for a patient. You might collect the wrong
data from a single another patient and you know, be
(11:06):
looking at it because everything was being done manually. You
were copy pasting image links with the patient links. There
was no single system where it was just collecting all
the data bringing it to towards the dentists and having
and I say dentists because on the review side, it's
also dentists that are involved and being able to provide
(11:26):
them that information.
Speaker 3 (11:27):
And then all the claims that were getting accepted.
Speaker 2 (11:30):
Or request needed requests from more information, they were still
going through this review. That means weeks were being spent
before decision was being made.
Speaker 3 (11:37):
And by being able to say, hey, here are the claims.
Speaker 2 (11:39):
That are like that can just be accepted, let's just
pay these out. Let's uh or after more information quickly
so that you know, people can provide the information as well.
And then here are the claims that might lead to
an adverse decision. Let's let's review those, but let's review
them thoroughly, uh a bit fast, you know, so you
don't want to spend forever on reviewing claim because that
(12:01):
cost can be that high because you know, again the
and the end the members are paying for it, right,
so the you know, the cost needs to be lower
and it needs to be consistent as well, So two reviewers,
you should come to the right solution. So the if
treatments needed should get paid if it meets the plant
guidelines should get paid and what does that need to
(12:21):
look like? And that's that was the contribution of overjet.
Speaker 1 (12:25):
Yeah, so let's just jump right in. I mean it
sounds like, with you know, the current market environment, it
sounds like you need to have a system that can
consolidate multiple other systems into one kind of cohesive platform.
So how does your platform work? How does overjet be
(12:47):
able to get all that information from the X rays
all the way to the insurance claims and being able
to go through that process into that one platform.
Speaker 2 (12:57):
Yeah, so we actually just hook into everything that that exists,
into the systems where they're scanning the paper dogs, into
the systems you know, my re clearing houses that they're
getting the information from. It might be their own internal
systems that they're connecting with. So being able to connect
with all the different systems that exist and being able
(13:17):
to then understand what the data is so you know,
where we can say, hey, this is a photograph, this
is an xt rate, this is a document, and that
helps saying okay, what do we need to do with
that information and where does it need to fit in.
And it doesn't come as a blob of data for
a reviewers, while it falls into like nicely designed templates
so that people can know, here, here's my photographs, here's
(13:39):
not you know, with the information is and be able
to then have claims return faster and then reduce reduced
costan make much more accurate decisions because there is a
pass of you know, it goes through and through this analysis.
Speaker 1 (13:56):
Okay, and so then I mean, so it's being able
to you know, high level be able to you know,
distinguish what's a photo, what's an X ray, and then
kind of what's a document and then I'm assuming within
that document then they can kind of say what is
a certain claim for you know, a cavity being filled
versus what's a claim for a root canal? And then
(14:17):
goes kind of even going further that because I'm assuming
these d s O s and these insurance companies they
have subtly different language for what can be covered and
what can't be covered. So how does the system be
able to be able to understand that subtlety?
Speaker 2 (14:37):
I would say that the organizations utilies in the software
configure the software for their needs. So you know, overget
is on deciding a claim whether it should fall here,
or for should fall in this bucket or that bucket, et, cetera.
It's a very configurable platform that allows for pairs to
be able to configure their plans. And it's actually very
(15:01):
interesting where you know, for example, in medicaids, you have
you have fifty different states. You might have fifty different
rules for for a single procedure. So you talk about hundreds,
if not thousands, of different rule sets that a company
is actually managing in their systems, and and and then
applying those rules based on what the uh, you know,
(15:23):
what state that claim is coming from, what plan the
patient is on UH, and many other checks which end
up determining different rules and edits okay.
Speaker 1 (15:35):
And so that's kind of on the payer side. Let's
let's kind of circle back to you know, the dentist,
the you know, the kind of the front line there
with the patient. You have you have these x rays.
What is Overjet providing in the analysis of those x
rays to kind of make it that objective decision on
if there is a cavity there or if it's just
(15:55):
you know, something else, or if it's worse than a cavity.
Being able to make those kind of you know, we're
talking about multiple dentists having multiple opinions about the same tooth.
How do we make that into that one decision?
Speaker 2 (16:08):
Yeah, So I think the interesting thing is, you know
why you could have multiple opinions is mostly around the
treatments as well. So you could have a cavity, but
you could do a filling, you could do a crown,
you could could do a root canal, you could do
a bridge, you could extract the two. There's like so
many things that you could do with it based on
the cavity. And the reason you might do one thing
(16:28):
or the other might depend on the structure of the tooth.
It might depend on the bone levels, it might depend
on how you know past history, you are there any restorations.
Speaker 3 (16:38):
On that tooth, et cetera.
Speaker 2 (16:40):
So being able to take take all that data in
and being able to say, okay, here's where you know
where the cavity is, here's outlining that out and sync
and how it interacts with the rest of the anatomical structure,
as well as if there are other restorations, et cetera.
Speaker 3 (16:55):
Coming to.
Speaker 2 (16:57):
And then utilizing guidelines to be able to say, okay,
if that's you know, if it is close to the
pulp you might need a root canal for example, and
how much to the pulp. You know, that's one where
you know there might be some variations that occur, but
once you can agree on what the guidelines are, you
can actually come to a very objective decision. So being
(17:17):
and and the way it manifests itself is it think
of it as if you've seen an extray. I think
of it as an outline that's outlining how much that
X ray is it's actually collecting, uh is, calculating.
Speaker 3 (17:29):
Ratios of that tooth.
Speaker 2 (17:30):
Area with how much the crown area of your tooth
is uh so cavity over the tooth area of the crown,
and being able to determine what the right treatment there
would be based on whether there's a pass restoration or
other conditions they are present.
Speaker 1 (17:48):
Okay, And so I mean, I guess when I'm thinking
of AI, you kind of have historical data of other
teeth and they've been labeled as a cavity or the
root canal or something like that, and then that gets
incorporated into the current image. Is that kind of the
machine learning that's taking place with the diagnostic portion of overjet.
Speaker 2 (18:07):
Yeah, So the interesting thing is the air part goes
on a lot of paid places. So the first is
what you call it image enhancement. So as images come
in and saying in dental practice, the quality of that
image might vary, might have been overexposed with radiation, there
might be less, they might be very bright and by
different contrasts.
Speaker 3 (18:28):
There you know, and there might be other just the
type of sensor, et cetera.
Speaker 2 (18:34):
So being able to enhance the image which in a
way that standardizes it based on the contrast and all
this other brightness and other pieces that need to be defined,
and we are FT cleared for that. That that AI
models are FDA cleared and very sophisticated in how they
enhance those images without impacting the clinical findings, so the
(18:54):
findings remain intact and it's able to remove the noise
from the image effectively. Then you have AI finding the
findings the clinical findings, then AI finding anatomical structures UH
and being able to identify those so it goes in
like different and then then you know you're doing all
the way from like key points to segmentations to detections
(19:18):
and other models that run to determine what type of
extra it is you know what you know and and
and so that you can run the very specific models
because we're trying to get to higher and higer accuracies
and and and surpass then just level accracies. And so
there's classification, detection, segmentation, you know, key points, all these
(19:40):
other models run that that get to the outputs.
Speaker 1 (19:43):
Oh interesting, And then you know we're talking about you know,
turning back to the payers again. It kind of all
circles back in with you being able to help with
the faster decision making for insurance claims. You also just
recently launched a new system called review Pass. So what
is review Pass and how does that help the whole
(20:04):
process even expedite or how does it expedite the process
even quicker.
Speaker 2 (20:10):
So I think review Pass is a game changer in
the industry. And what it does is it gives an
ability to the provider, with the click of the button,
be able to skip the manual insurance review. And that
is so beneficial for the patient for example, because rather
than waiting thirty days and getting a surprise bill at
the end, they are getting a decision within less than
(20:32):
a minute, and that gives them a lot of confidence
in what treatments that are being recommended by the dentists,
how insurance will will reimburse them, and how much they
will have to pay out of pocket, because again, having
this surprise bill of one thousand dollars is for a
crown for example, is very hard for many Americans to
(20:55):
be able to pay for. And by being able to
have that information right there, knowing an s in it
around what insurance book is very important. So review pass
is very important for that. But it's also helpful for
providers because they spend a lot of time trying to
get eligibility and benefits of information, trying to get information
from the provider around the treatment that needs to happen.
(21:18):
By being able to then have that data just being
present within in less than a minute with the press
of a button, stops them from calling forty five minutes
into a dental office and collecting this information and it's
right there as well as for the insurance companies because
you know, if providers are calling, payers are listening or
(21:38):
and talking back as well, so you're spending forty five
minutes there as well sharing of information of that patient.
And how do we actually make that seamless? So and
I think it also leads to having everybody more aligned
and having more trust in the system as well.
Speaker 1 (21:55):
Yeah. No, absolutely, especially when you kind of have that
comfort level that the decision you're going to make is
going to actually go through the insurance claims properly. Now,
this sounds like the other end of the spectrum that
we just kind of talked about a few minutes ago
about all the previous X rays that have been analyzed
as kind of the data the input values for the
(22:16):
new output, which is the current patient. This is going
the other way where it's are you reviewing hundreds and
thousands and thousands of previous insurance claims and seeing which
procedures got covered by particular insurance companies and then kind
of going through that process of evaluating whether or not
(22:37):
there's a probability that that would be covered for a
future procedure.
Speaker 2 (22:41):
No, here, we're actually connecting directly with the BEAR system
and getting a response back in real time. So this
isn't you know, us guessing. This is us bringing the
BEAR system, getting a response back, and being able to
then display that response to the provider. And in order
to be able to do it, we had to work
(23:03):
with the pairs to have their systems be real time
there you know, every everyone had batch processing, everyone had
you know, uh, this process is a week multiple week
long process. That we were able to shrink it down
to less than a minute and be able to bring
that to life. So it is you know, pretty fascinating
(23:25):
to see how how pairs were able to make that
happen and how providers were able to help them to
make that happen as well.
Speaker 1 (23:33):
Oh that is interesting, Yeah, because I was assuming that
you guys were making the best guess based off of
all the data yet, but this is now you're already
communicating with the payers at this point already.
Speaker 2 (23:44):
And that's what the future should be, right Like you know,
in today's day and age, why should we submit things
which you know, mail things in and wait for things
to come back like we have digital communication and and
APIs that can talk back and forth. There's a lot
of infrastructure to be built in to be able to
do this effectively, but you know that's where and to
enable the yeah, to make this happen. But you know,
(24:07):
I think there is appetite on both sides to do so.
Speaker 1 (24:10):
Yeah, no, absolutely, I agree with that. And so this
kind of was going to roll into my next kind
of set of questions about kind of the commercial rollout
of Overjet. But I'm going to just start continuing with
this payers, you know, the the review pass, because you
already need to have a relationship with some of these payers,
they already need to be on board. So kind of
(24:32):
what percentage of covered lives you know, do you already
have covered under this review pass with having you know,
payers be on board already?
Speaker 2 (24:42):
Yeah, so so Overjet serves majority of the top insurance
companies representing about one hundred and thirteen million lives. For
the review pass we have about this is you know,
again brand new, first time ever being introduced as and
pairs basically saying we're in for the ride and taking
(25:04):
a risk on us and taking a risk on and
having faith in in dentists to do the right thing
and exposing these systems and making sure that in the
end the members actually benefit for that. We have pairers
represent about forty million members and these are pairs like MetLife, Humana, Guardian,
(25:26):
et cetera, who are saying, hey, we are going to
be at the forefront of this UH and spend resources
to make sure that we are providing better service to
our members and improve the provider pair friction that exists.
And then we have provider groups as well taking part
(25:46):
in making this happen because we want to do it
at scale to start off with. So you have companies
like Dental Care Lines, Interdent, North American Dental, Smileless, Core Dental,
et cetera. We're saying, hey, we were going to participate
in this as well and figure out all the kings
and figure out all the areas and really start to say, hey,
what's how do you work on more experience as well
(26:09):
and really build us out. You know, this is I believe,
the first step, and there's many more steps to be
had here.
Speaker 3 (26:17):
Yeah.
Speaker 1 (26:17):
No, and that's all interesting. What got my attention though,
is well, we talked about previously about how the antiquated
way of you know, insurance companies covering claims and you
would have to have sometimes two people in the in
the company kind of reviewing the same claim because you
want some you know, the balance the quality and the
speed and everything. But this sounds like by you know,
(26:39):
having the review passed and having it kind of already
you know, it takes one minute to kind of get
that approval and you don't need those two employees anymore
wasting their time doing one claim. They can go and
do other things to help out with the insurance companies
and other various aspects of the efficiency of pain out
for these patients. And so then you're talking about the
(27:01):
dental companies, the DSOs as well getting on board. I mean,
how long has Overjet been out in the market at
this point.
Speaker 2 (27:10):
So we started the company started in twenty eighteen, so
August twenty eighteen, so been it's been a while here.
We started selling to dental practices in We got our
first of declarance in twenty twenty one and really started
rolling this out in twenty twenty two.
Speaker 1 (27:27):
Okay, So how has that rollout over the last two
two and a half years, Ben? And how has that
built the foundation now for this review pass as you
kind of get that launched off the ground.
Speaker 2 (27:39):
I think for us now we serve nine out of
the top fifteen dental service organizations with the larger groups there,
we also serve a lot of you know, solar practices,
thousands of solar practices as well, and as we roll
out review Pass, we are also partnering with other companies,
(28:01):
other practice manishment systems who are just distributing this across
their member base as well. So, so it is you know,
utilizing that customer base we have and then customer base
of our partners to be able to launch this across
the United States.
Speaker 1 (28:20):
Yeah, and then so and then how how is the
commercial team built out to be able to expand that?
Is this something there you have to have sales reps
knocking on door to door at each dentist office, then
going to the insurance companies or is there a new
way of being able to have this kind of outreach?
Speaker 2 (28:39):
Yeah? So I think with the review pathel, we're right
now offering it to our customers. So these are not
new customers yet. Uh, as we expand that further, we
will you know, I offer to other folks as too,
either sorry our customers or our partners customers. And but
(29:00):
in general, like how we get to customers is through
inbound and outbound sales, and there's a lot of you know,
people who reach out to us as well on our
website and schedule a demo and then get on board.
The good thing is most of it happens virtually, and
that helps to scale much more effectively.
Speaker 1 (29:21):
I was about to say, yeah, you don't have to
travel to each dentist in the state or the county
or anything like that. So then you know, we're talking
about review pass and I know that it just came out,
but I'm assuming that this is not it for product
development for overjets. So kind of what are some of
the next developments beyond that that you're working on to
(29:43):
make this a more holistic approach for the kind of
the dentists and for the payers.
Speaker 2 (29:48):
Yeah, so this is part of what we call the
Dental Clarity Network. So we actually introduced an inter or
cross industry collaboration around reducing the provider and bear friction
and reducing the cost in current as well. So which starts,
you know, with eligibility and benefits automation, so in short,
verification automation, review pass, claim submissions automation to reduce that
(30:14):
overhead for customers credentialing. You know, that's also a pain
point between providers and pairs. Being able to work on
these pieces which you know, which either originated on the
provide sid or originated on the pair side will cause
a lot of friction between the two and being able
to solve them through technology and partners who are really
(30:35):
committed to a better member and provider experience.
Speaker 1 (30:39):
Yeah. No, that kind of goes back to that whole,
you know theme that we're talking about through us an
entire half hour so far has been just subjectivity versus objectivity.
And if you have two people budding over how much
that you want to pay or if they're going to
pay for it, if you gain all that data to
be able to say, hey, this is actually what it is,
this is what it has been historically paid for, you
don't have to worry about that butting of heads anymore.
(31:00):
And so we're kind of going then back to the
review pass. I mean, we're just launching it here in
March of twenty twenty five. When you come back onto
this show in March of twenty twenty six, what how
do you how do you see that ramping up in
that kind of twelve month time frame.
Speaker 2 (31:22):
So I really do think that in a year or
so we can completely eliminate what it's called ROUNDEUS cycle management,
and that is, you know, this idea of introance verification
and claim submission and eobs and like dealing with all
(31:42):
this paperwork and their teams like there are hundreds of
people in these organizations dealing with that information, and can
we actually have that these this administrative work be automated
and can we have this so it says that there
is reduction costs as well as accuracy in these systems.
(32:03):
I think that's very possible in the next year and
be able to then, you know, hopefully utilize these folks
towards you know, you want them communicating with patients. You
want them helping patients get the best care, not dealing
with paperwork. And how do we make that happen?
Speaker 1 (32:23):
Yeah, and you know what, I would love to see
that happen down the road because yeah, just you know,
from my experiences too, not knowing what exactly you're gonna
have to pay for until you kind of put out
your credit card for the out of pocket payment. Definitely
would like to have that more information like that in
the future, you know. As we close up, though, you know,
it's a great story about how you came to found Overjet.
(32:47):
One of the things I like to ask guests on
the show is you know, was there a specific book
or group of books that you've read over your time
at school or recently that's helped you be able to
drive over Jet to where it is today.
Speaker 2 (33:06):
I would say I constantly read books which help in
building of the company and uh uh and managing off
the off the people, et cetera, and and different scale
of the company. There's different books that come into play.
I think one of them which has been very instrumental
UH is a clear use scaling people really around you know,
(33:30):
how do you manage much more effectively in build systems
around it? I think, UH, there's a book on Amazon
working backwards has been very useful as well. I recently
read a book Sales Acceleration Formula around how do you
scale up the teams, which is I think really helpful
for growth. So I think at different stages, you know,
(33:50):
different books have helped in shaping how Overjet has uh
has evolved, as well as how I view company building.
Speaker 1 (34:00):
Nice and I think that's a nice little spring break
reading while you're at the beach and everything. Yes, but Wada,
thank you so much for joining us today. This was
a very thoughtful conversation we had today.
Speaker 2 (34:12):
Oh, thank you, Matt, thank you so much for having me.
Speaker 1 (34:15):
And thank you to our listeners for tuning in today,
and we hope you join us for future episodes. If
you would like to stay up to date, you can
click the subscribe button on Spotify or your favorite streaming platform.
Take care
Speaker 2 (35:01):
Lass
Host
Jonathan Palmer
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