November 10, 2025 • 33 mins
Thanks for tuning in to these conversations with two founders changing the future of healthcare live from HLTH 2025.
Zachary Ziegler, co-founder of OpenEvidence, built a platform that reached 40% of practicing clinicians in just two years by centering a simple principle: every answer includes citations to peer-reviewed research. With access to 40 million papers updated daily with 10,000-20,000 new studies, doctors can verify every claim instantly. Growing 30-40% month-over-month and adding 60,000-70,000 clinicians monthly, Ziegler challenges conventional wisdom—EHRs are already a top burnout driver, forced integration isn't the answer, and physicians prefer autonomy over mandates.
Dr. Aditi Joshi, founder of Ardexia, tackles a different crisis: healthcare organizations waste $87 billion annually on contracted technology doctors never use. A former emergency medicine physician who experienced burnout twice, she moved into telemedicine and discovered the core insight—most builders don't understand how physicians actually work. You can't mandate adoption. You can only solve real problems. She's building Ardexia with validation first, burnout prevention as a foundational business strategy, and clinician expertise leading product decisions from day one.
Highlights from Zachary Ziegler at OpenEvidence:
- Started with a Harvard PhD studying language models before ChatGPT; built "ChatGPT for doctors" with complete citation trails to peer-reviewed research
- Reached 40% of practicing clinicians with daily active usage; adding 60,000-70,000 new clinician users monthly (30-40% month-over-month growth)
- Philosophy: "Trust, but verify"—every answer sources from original papers so doctors can verify claims against peer-reviewed research
Highlights from Dr. Aditi Joshi at Ardexia:
- Former emergency medicine physician who discovered during telemedicine work that technology adoption is a people problem, not just a technical problem
- Identified the $87 billion annual cost of unused healthcare technology—five-year contracts continuing whether clinicians ever use the tools
- Building Ardexia with burnout prevention as a foundational business strategy; validation-first approach to understanding specific pain points before scaling
The result: healthcare's AI transformation doesn't happen in the lab—it happens when builders center the people actually using the tools.
A "glow up" signifies a positive transformation, reflecting the journey of becoming a better, more successful version of oneself.
At The Tech Glow Up, we humanize the startup and innovation landscape by focusing on the essential aspects of the entrepreneurial journey. Groundbreaking ideas are often ahead of their time, making resilience and perseverance vital for founders and product leaders.
In our podcast, we engage with innovators to discuss their transformative ideas, the challenges they face, and how they create value for future success.
If you're a founder or product leader seeking your own glow up, or a seasoned entrepreneur with stories to share, we invite you to join our guest list via this link.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Zachary Ziegler (00:00):
everything that we say as part of answers is
(00:02):
always referenced.
So there's citations toeverything.
And so you don't actually haveto trust AI at all to get value.
Use Open Evidence because youcan always verify, everything.
And so our motto, here, istrust, but verify.
And that's really central toOpen Evidence.
Nathan C (00:16):
So, you ready?
1, 2, 3.
Hello and welcome to the HLTHTech Glow Up.
I'm Nathan C and today I'mtalking with Zachary Ziegler,
co-founder of Open Evidence.
Zach, it's so great to meet you.
Thanks for joining me on theHLTH Tech Glow Up.
Hello.
Amazing.
(00:36):
So, to get started, can youintroduce yourself and the work
that you're doing at OpenEvidence?
Zachary Ziegler (00:42):
Yeah.
So I'm Zach.
I'm the co-founder and CTO ofOpen Evidence, we essentially
make, Chat GPT for doctors.
We become the fastest growing,most rapidly adopted, AI tool
used by clinicians.
we're now used by over, 40% ofpracticing clinicians with the
average user using us, everyday.
Okay.
my background is technical.
(01:03):
I'm, I'm an AI person.
Mm-hmm.
I come from a PhD program atHarvard, where I was working in
the pre-chat GPT days on,language models and generative
modeling and all that stuff.
and yeah, I got reallyinterested in how do we make
these models do somethingactually useful?
How do we make these models likeactually impact the world in a
meaningful way?
and yeah, ended up, you know,here we are.
Nathan C (01:24):
Were you always interested in healthcare as an
application for large languagemodels, or did that focus come
out of the research that you didin building, the idea?
Zachary Ziegler (01:39):
Yeah, so ultimately what motivates me is
just making useful stuff.
That's always been just thething to just really make things
that people love and people use.
And what struck me early on,myself and my co-founder Daniel,
was that, healthcare sits inthis space that is, In so much
red tape and bureaucracy.
when we were getting startedwith this, it was one of these
last very obviously yellow taxicab era style, industries, Where
(02:03):
even as consumers, it was wildto us that if you want to know
what is the science actually thebreast resource is, WebMD.
Mm-hmm.
Which is crazy because it isliterally a meme.
right.
That you go to MD and you ask,but you have, and it'll tell you
you have cancer.
Yeah.
and, and the, what the, theshame is, is that there's so
much that we know as a species.
I don't think people appreciatehow much medical knowledge
exists and how much researchexists.
(02:25):
there's 40 million papers.
There's.
10 to 20,000 new or updatedpapers every single day.
It's an enormous amount ofliterature.
Nathan C (02:32):
almost like a YouTube.
I mean, that's a similarcontent.
Sure.
Fee.
Yeah, that's right.
Zachary Ziegler (02:36):
huge amount of, context area, and yet there's no
real ability to access thatknowledge.
And so we made Open Evidence tobe kind of a bridge between
people who have needs, whetherthat's, originally kind of when
we were.
Considering this, for WebMD kindof consumer stuff, but very
quickly, you know, really,focused on the physician side.
and providers, to bridge the gapbetween providers who need
(02:57):
access to the, best, informationand the best care.
And that information that reallydoes exist in the home.
That's amazing.
Nathan C (03:05):
Could you, for the sake of those who maybe aren't
in the health tech space, talkabout your data sources and, how
you collect the research and,what is it like for a doctor to
use, Open Evidence?
Zachary Ziegler (03:20):
Yeah.
So, we pull data from a bunch ofdifferent sources and we do it
in a bunch of different ways.
Probably the most important datathat we work with is our first
party content partnerships.
we have, partnerships with, theNew England Journal Medicine
jama, and a whole bunch of,societies as well.
these are the absolute top ofthe top, the biggest gold
standard for, clinicalinformation.
This is where the.
Best phase three clinical trialsare published, and really the
(03:43):
most kind of world changing,aspects of, of medical knowledge
exists.
So it's really important that wehave, those deep partnerships.
we're able to kind of show anduse figures, especially in
multimedia from those which arereally cool.
and we're working on kind offurther collaboration with those
as well.
Nathan C (03:59):
That's like dimensions that audio or like other modes.
Might miss out on Yeah.
like, speaker's, slides and somerecorded CTA thing or something.
amazing.
So, my kids are like ultimate AIskeptics.
Yeah.
And, I've even heard at theshow, right, people talking
about, hallucinations are real.
(04:20):
I'm sure you've addressed it,but I'm hoping you can talk to,
like what are the risk factorsfor being an AI layer for like
medical research andinformation, especially like
when you're working with doctorsand advising or, you know, kind
of.
Affecting how they're makingdecisions about care.
Zachary Ziegler (04:39):
so the way that we approach this problem is we
focus on search essentially.
Is the answer, right?
There's traditional approaches,chat BT might imagine, right?
Which is like big black box,throw some questions and just
like hope that you get goodanswers.
We take a very differentapproach, which is essentially
the bottom up to that top down.
So we, we really, at the end ofthe day, we do search.
That's what we do.
(04:59):
And so what that means is whenusers have questions or clinical
cases, we will find the exactright sentence, paragraph, we
see our job as really beingsearched, just surfacing those
pieces, to humans.
And then largely what we use,kind of what people today think
about AI for it is, makingreally great search and then
also providing a layer offluency and conversation on that
(05:20):
just for a kind of convenientexperience.
And so what that means is thateverything is from the bottom
up.
Everything is about, You know,true what humans have said, what
humans have written, what humanshave published and gone through
peer review.
And then also the side effect ofthat, which is just as
important, is that everythingthat we say as part of answers
is always referenced.
So there's citations toeverything.
And so you don't actually haveto trust AI at all to get value.
(05:43):
Use Open Evidence because youcan always verify, everything.
And so our motto, here, istrust, but verify.
And that's really central toOpen Evidence.
Nathan C (05:51):
Do on the platform side, you potentially have, this
is like just riffing.
ability to understand howfrequently doctors are actually
clicking in to those references.
Is that something you're able totalk to at all?
Zachary Ziegler (06:07):
don't know the exact number, but it's, it.
It is really quite frequent.
it's, you know, it's, it'sreally important, right?
if you're a doctor seeing apatient, you are responsible for
making the decision.
There's nobody else.
And so Open Evidence is a placethat people go because it's
just, one layer of support.
That's a really common kind ofuse case.
but at the end of the day, thestakes are high.
There's someone there insomeone's life, right?
In principle, in the worst case.
(06:28):
And so, having that ability tolook through and double check
and go to the references andsee, exactly what the, original
source material said.
I can't imagine practicing usingany kind of AI tools without
that foundational support.
Nathan C (06:43):
The, I would say that like one of the themes I've been
seeing at health, like overallYeah.
Has been like ai, but there'sstill a human.
Totally.
And in many cases that's part oflike the rebuttal page for an AI
product.
Yeah.
Right.
Like, but there's a human inline or we have this person, or
(07:05):
there's a trans.
Later.
And what, what I kind of findreally elegant about what you're
describing is that the humaninvolved is the customer, is the
doctor doing the search?
And so it's built in to the workflow that the human is always
gonna be at the front.
(07:25):
Yeah, because you're notnecessarily like asking for a
diagnosis, you're not asking,right.
Like you're asking for theresearch.
You're asking to get right tothe specific thing that I really
want to address.
First and then that ability tohave a conversational.
interface to the research, forsomebody who can make a
decision.
Zachary Ziegler (07:45):
Yeah.
Nathan C (07:46):
And, I'm sure people much, I'm not even gonna get
into the, like, models canhallucinate even if they're day
like.
there's something, but I lovethat there's a safety layer and
just like an elegant, asimplicity of the technology
That align very well, in thismodel.
So it's,
Zachary Ziegler (08:02):
very cool.
There are, questions, whateverconcerns when AI is framed in a
way that is kind of aboutreplacing humans, right?
Mm-hmm.
And that's when you startgetting into like, okay, we're
gonna start with some human inthe loop thing.
Mm-hmm.
And eventually we're gonnaremove that and replace that
human with position.
That's really not at all how wethink about this, right?
We really think about this AI asjust a tool that is.
(08:25):
Supportive of physicians.
we don't think about it in termsof replacing.
we also don't even think aboutit truly in terms of even saving
time.
There's, another common thing islike, AI is gonna save time for
physicians.
And the reality is that's, thenwhat happens is immediately,
health systems just startcompressing schedules and giving
more and more, patients to eachphysician.
So what we think about at theend of the day, or maybe they
play wordle well, there's noguarantee that it's.
(08:47):
Go into efficiency or, physicianlines are hard enough.
Yeah.
You don't, these, for-profithospital, these are efficiency
machines.
They're just going to, anyamount of save time really just
increases, the amount ofpatients people have to see.
So, what we care about and whatwe focus on truly with Open
Evidence.
Is, how do we make doctor liveseasier?
How do we make it just notfaster, but just truly easier to
do their job?
Nathan C (09:07):
There's a little bit that you hinted at about like
leveraging information to combatsome of the challenges of the
weird.
Investment structure inhealthcare, that I'm not even
gonna touch, but is like supercool, like some very interesting
ideas.
so thank you for that, Zachary.
(09:28):
This is like, such a cooltechnology and to have 40% of
practitioners in a daily,actually, how long did it take
you to get to daily use, like.
Zachary Ziegler (09:38):
Yeah, well we, so we started about two years
ago.
Mm-hmm.
Releasing Open Evidence.
But it's really just in the lastyear that we have absolutely
exploded and taken off.
We've been growing about 30 to40% month over month.
so, you know, in our early daysthat was, small numbers.
But the nature of exponentialgrowth is all of a sudden that
gets very big, very fast.
we're adding 60 to 70,000clinicians, per month at this
(09:58):
point.
and it's fantastic.
we, you know, we're thrilled tobe making a difference and to be
making, really fantastic tools.
Nathan C (10:05):
60 to 70,000 a month gets.
To millions really fast.
Yes.
That's cool.
amazing.
so let's, let's go a little bitbigger.
let's look at the industry.
Look at why we're here.
the podcast we're on right nowis the HLTH Tech Glow Up.
A Glow Up is a notable rebirth,a transformation looking at the
(10:26):
healthcare industry, like you'realready solving some of these
core problems and like workingon some of these hot issues.
I'm.
Curious what's, what's theperspective, what's the goals
that you have, for healthcare,for practitioners?
what's the big audacious goals,that you have for healthcare and
health tech, in the next sixmonths to a year?
Zachary Ziegler (10:44):
Yeah.
Well, I think it's this reallyinteresting moment where it
feels like kind of all the dusthas been kicked up and there's
questions around like, how todescribe, play into things,
right?
How do, clinical copilots playinto things?
Does integration matter?
Does integration not matter?
Right.
And so I think, you know whatI'm, what I'm really intrigued
by is like where, you know, howdoes this all land?
Kind of like what is, what, asthis kind of normalizes into,
(11:07):
into physician flows, like, youknow, healthcare is an
enormously varied, so.
Base, right?
It's not just one thing.
Practice looks like enormouslydifferent, in many different
situations.
And so I think there's, it's areally exciting moment where
it's never been easier to buildAI tools, right, or to build,
any tools at all with just howfast it is, increasingly to
(11:28):
build products.
and so I think it's a reallyinteresting opportunity to, run
as fast as we can at buildingthe most useful tools for
physicians, to make stuff thatreally find the places that can
help every physician.
I'm especially reallyinterested, for our part in, you
know, how far can we push thesemodels?
How far can we push medicalreasoning?
How far can we push, medicalintelligence?
Can, you know, is there anythinglike that really starts to
(11:49):
approach medical superintelligence that we can, that
we can build with a con with.
The, with the, you know,foundation of the literature and
guidelines and practiceinformation.
but as we especially level upreasoning and, and, and those
sorts of capabilities.
So that's what I'm reallyexcited about.
those are, we're working on someof that stuff and we'll see,
see, can, is
Nathan C (12:05):
there, not to pin you down to any of these specific
goals, but for medical superintelligence, what would be the
first problem you would gosolve?
Zachary Ziegler (12:16):
Well, the reality is I think it's a big
spectrum, right?
There's Open Evidence like issuper intelligent from a like.
in specific instances, right?
The ability to, have 40 millionpapers condensed into one tool
that you can kind of query fromand get access to is something
that,
Nathan C (12:32):
an executive summary is pretty good.
Zachary Ziegler (12:34):
can't do that, right?
So there is, there is somethingthat a lot special about that.
But there are also plenty ofaspects that I don't think we're
gonna recreate for a very longtime, right?
I think human intuition,physician intuition, and
experience is so important andso critical.
I think we'll figure out how tomesh, continue to mesh those
pieces.
Nathan C (12:50):
Yeah.
that's gonna be my new ai.
Amazing.
you kind of actually answered, alittle bit about the Glow Up for
Open Evidence.
You teased this question thatlike I have to come back to, are
integrations important or arethey not?
do you have an opinion on that?
Zachary Ziegler (13:09):
I think they're okay.
I don't think they'reexistential, I don't think
they're critical.
You know what, when I talk toclinicians, what I hear is the
core value, the core thing thatis really important is being
able to just get fast answers,fast, trustworthy answers to
questions, right?
The idea that you can pull outyour phone when you're standing
outside the patient room, ask areally challenging but important
(13:31):
question and get an answer rightaway, that is easy.
It's that ease of use.
I think that's the thing that wealways push for ease of use and
low barriers.
I often cite ease ofintegrations as the fastest path
Yeah.
To ease of use.
Yeah.
And like meeting customers wherethey are.
Yeah.
but if you're in a world whereyou can build AI tools quickly
(13:56):
and a doctor actually doesn'tmind pulling out their phone to
like get the answer that theyneed in the moment, and maybe
that's their preference.
change it if it's not, if it'snot broken in healthcare
especially, right?
Like physicians are essentiallyjust like.
they are force fed EHRs, andit's like, you know, one of the
most like interesting, wellcited facts that I keep coming
(14:18):
back to, and it's just like I,it keeps bo bopping around in my
head is that like EHRsthemselves are cited as like one
of the top three causes ofburnout by physicians, right?
I mean, one.
Crazy profession to live inwhere the technology that your
administration is often forcingon you is the very thing that is
like, I have to click all thesebuttons.
It's a huge pain in the ass.
Why do I have to do this?
(14:38):
and so for physiciansspecifically, I don't think they
all.
Love their existing EHRs, andI'm not sure they're like, boy,
what I really want is more, eh,HR.
You know what I mean?
Yeah.
Nathan C (14:48):
EHRs are the TPS reports.
Health tech is what I've justlearned there.
Zach, you're pushing on some ofthe conventional wisdom that I
like to talk about in a coupledifferent areas.
Yeah.
I'm trying not to be upset aboutit.
Let's jump to the next thematicquestion as a diversion.
(15:09):
The theme for the show this yearis Heroes and Legends, and I'm
using it as an opportunity toask people about the mentors,
heroes and others, both inhealthcare and in innovation.
Sometimes just having one personbelieve in you and say, keep
going, can, like, havetransformational effects.
(15:31):
And so I'm using thisopportunity to try to get to
those stories.
Are there people who, ororganiza, you know, heroes,
legends in any way that haveinspired you on your journey as
an innovator?
Zachary Ziegler (15:45):
well not, not, maybe not quite mentor
specifically because I never metthis person.
but in terms of, A guidingfigure.
Yeah.
I think a lot about, Steve Jobs.
Yeah.
and specifically in thehealthcare sense.
Oh.
Because, do you know what thetechnology that was the fastest
adoption technology before OpenEvidence was among physicians?
Nathan C (16:06):
based on the context, my guess is gonna be the Apple
Watch iPhone.
Okay.
Zachary Ziegler (16:12):
that was, you know, like we're in now with
this AI movement where there's,so much, happening so quickly.
Right.
In so much, like I said, up inthe air and changing.
That was a previous periodwhere, there was this.
introduction of new technology.
I was just talking earlier withsome positions that were
talking, when they got theirfirst iPhone.
First it was an iPod Touch andthen an iPhone, and what a
change that was to, level upfrom textbooks to all of a
(16:35):
sudden, still set of content,but just have that right there
in your pocket.
and so, you know, that's a.
Cool.
kind of like precursor in a lotof ways that mirrors a lot of
this, but, you know, and thenjust as an individual, right?
Like Steve Jobs is absolutelyincredible and I think he has
some of the best, kind ofphilosophies for building a
company, for innovating.
And, and, yeah, he, he'sabsolutely.
(16:57):
Inspirational figure for, forhow to build things for real and
make things in practice.
Nathan C (17:01):
I love that there's like a, I love Steve Jobs as a
hero there because there's thislike uncompromising quality and
focus on design.
Yeah.
So, last question, and it'stotally optional.
What year was that adoption?
I dunno.
Dr.
Lee.
We are like, one minute I have
Dr. Lee Glasser (17:20):
to go on the
Nathan C (17:20):
call.
Dr. Lee Glasser (17:20):
I'm er, I was friends with Danny.
Okay.
Yeah.
And I'd love to talk you, it's aformer Chief Medical CMS and I
know a lot of work.
Amazing.
And reasoning and writing.
Yeah.
Yeah.
How to educate the nextgeneration of yeah.
Talked to George Daley about, Idunno if you know George?
No.
Harvard Medical School.
Oh, okay.
Yeah.
So your team has my number.
(17:42):
Okay,
Zachary Ziegler (17:42):
Yeah.
Dr. Lee Glasser (17:43):
Okay.
Zachary Ziegler (17:43):
Awesome.
Dr. Lee Glasser (17:43):
heard you spent some time with Danny.
Zachary Ziegler (17:45):
yeah, my co-founder for Luxury.
He became your friend.
He was special person.
Yeah.
Nathan C (17:51):
Smartest
Zachary Ziegler (17:51):
man I've ever met.
Hey you.
Nathan C (17:52):
Hell yeah.
Harvard Connections live on theGlow Up last question, Zach, and
it's totally optional.
Do you have a spicy healthcarehot take?
Zachary Ziegler (18:06):
I don't know actually if this is a hot take.
But I think that AI is onlygoing to extremely, positively
impact all of our lives.
there's so much, concern andfear, right?
And anxiety around ai.
Is it taking people's jobs?
is it leading to ai slop, If yougo on the internet, it's almost
exclusively negative, right?
Open Evidence shows that thereare ways for it to literally
(18:28):
save lives, right?
for it to impact the world at avery large scale in a way that's
extremely positive.
It's very easy to be negative onstuff and it's very easy to
point out problems.
I think we'll look back a year,two years, three years, and
certainly much farther than thatand see this as a really
important step function for thewhole world.
I see that in the clinicianspace for Open Evidence.
(18:49):
I see that as an engineer incoding tools.
and I think as this percolatesfarther through to society and
people start.
Seeing the reality every day aspart of their jobs.
It's going to be very clear justhow positively beneficial AI can
be for the whole world.
Nathan C (19:04):
I'll take it.
some of that sentiment remindsme of some things that, Alvin
Wang Graylin, talks about.
I don't know if you're familiarwith Alvin, he's a, former
leader at HTC, but very much,interested in AI in this
direction.
Zach.
It's been fantastic, to chatwith you.
Thank you so much for sharingsome of your very busy day.
(19:26):
Yeah.
here at HLTH and, you know, justfantastic work.
I think, that optimism of howpowerful AI can be has gotta be
partly a product of.
How incredibly successful you'vebeen able to be in the last four
years, building with it.
Right.
And while many of us are stilltrying to find our paths, you're
(19:46):
here trailblazing, with outcomesand like centering doctors in a
way that a lot of folks seem tohave a hard time doing.
So Bravo.
Well thank you and thanks forjoining us on the Health Tech
Glow Up.
Thanks for having me.
Amazing.
We got one last thing.
We're just gonna clap it out.
Okay.
1, 2, 3.
Amazing.
(20:08):
So one, two.
Awesome.
Hello and welcome to the HealthTech Glow Up.
I'm Nathan C, and today I amtalking with Aditi Joshi of
Ardexia.
Aditi it is so good to see you.
Thanks for joining me on theHealth Tech Glow Up.
Aditi Joshi (20:24):
Thank you.
Thanks for having me.
And hello everybody.
Nathan C (20:27):
Amazing.
Can you introduce yourself andthe work that you do at Ardexia?
Aditi Joshi (20:32):
Yes.
Thank you for calling me anicon.
I'm gonna live off that now, but
Nathan C (20:35):
yeah,
Aditi Joshi (20:35):
so this is a new company for me, and we've known
each other for a few years, weknow what we want to do for
healthcare, but it's just nothappening.
So looking back at like whateverything I've built and I
realized that it's.
We've got great technology.
People really want to helphealthcare.
We have leadership and laws andeverybody's involved, but we
still haven't been able toreally get doctors who want to
(20:56):
use it successfully.
There are health systems, thereare government programs, there
are clinics.
People are sitting on technologythat isn't being used.
And so I thought to myself overthese last 12 years.
What has worked, what have Iseen actually work to get
doctors to actually want to useit.
And that's what we're doing andwe're fixing.
Nathan C (21:16):
Are you able to share what it is you've seen that
doctors actually want to and douse?
Aditi Joshi (21:24):
Yes, I will say that.
the biggest problem is thatpeople don't really understand
how doctors work.
The biggest take is that wedon't really have bosses.
We have people who haveoversight, but once you're at
the standard of care, we don'treally have bosses.
We are able to see our patientsand decide what we wanna do.
We have to do the right thingfor them, but that's it.
(21:44):
So you can't actually go into ahealth system.
You can't be like, Heyeverybody, you've gotta use this
tool.
If there's a tool that alreadyworks and is great for patient
care, you cannot force us to doit.
It's just not happening.
You have to look at what are theactual pain points?
What do we want better forpatient care?
What is the actual behavior andpsychology of the doctors at
that practice that's stoppingthem from using it?
(22:05):
What are the real pain points?
Who's the leadership?
You gotta think about all ofthose things.
Nathan C (22:10):
My suspicion is like, just for the sake of example,
right?
Like a podiatrist and a oncologydoctor are gonna have incredibly
different drivers, even thoughthey might sort of have some of
the same credentials or youcould put the same labels on
them.
Aditi Joshi (22:28):
Yes.
Nathan C (22:29):
so what's your approach for helping
technologies better understandand activate doctors?
Aditi Joshi (22:39):
So I put it out, I looked at my playbooks and it
just basically.
Put it out there, and I figured,all right, these are the steps
that you need to take.
So the first thing we have to dois actually validate it.
And I'll tell you, Nathan, Iknow it works.
I have done it multiple times,but I need to make sure that it
works in this context.
And then once I do it, I'm gonnabuild an app around it.
So looking for any techco-founders, if you know anybody
(22:59):
who might be interested.
Nathan C (23:00):
interesting.
Have, this is totally like,curiosity around innovators and
the choices they make in,excited circles.
There's a lot of people that sayyou don't need a technical
co-founder anymore because youcan prototype and.
Create a number of like proof ofvalue apps with AI code
(23:22):
assistance.
what's your thoughts as afounder?
Aditi Joshi (23:25):
I'll say that AI has come really far and it's
actually really exciting whatyou can do with it.
But I will fully admit this.
I have taken on a veryambitious, complicated problem,
and so I did actually trycreating an.
App using the playbook that Idid.
it does part of it, but it doesnot get everything that I want.
And so I know that I'm gonnaneed somebody who has a little
bit more experience to makeexactly what I'm looking for to
(23:46):
do.
Nathan C (23:47):
Yeah.
along with that intuition andthat experience.
Right.
Like back to the, the top, like,I've done it before.
I've seen what works.
I'm, I'm curious, you're kind ofmultihyphenate.
You've got these many strengths.
what was that, origin story,that moment that inspired you to
kind of take this innovationpath when you have so many tools
at your disposal?
Aditi Joshi (24:08):
Oh, yes.
So I'll say that in general.
Emergency medicine, we tend tobe innovative because we have to
think on our feed.
We have to really make surethat.
We're going in the rightdirection, and if it's not, we
gotta change paths.
But really my story was I gotburnout and I really could not
work in the emergency room atthe level that I was doing or
the amount of time that I wasspending there.
(24:29):
And so I was looking for otherthings and I applied for a
telemedicine company and I justreally loved what they were
trying to do.
And I will tell everybody this,You cannot just try to escape
your burnout by going into afield like this unless you
actually love it.
I actually loved it.
I found it useful.
I understand how we improveaccess to care.
(24:49):
I saw patients, I have multiplestories where I helped them and
really understood what it's likefor patients at home, which I
don't see in the hospitalsetting.
And it really gave me anunderstanding of what technology
can really do to help people intheir homes.
Nathan C (25:02):
So let's look at the conference and the setting that
we're in, sort of dive in, toHTLH itself.
I use the idea of a glow up or anoticeable transformation or a
rebirth.
As a way to talk about goals.
Mm-hmm.
and how we grow into the future.
Thinking at the industry level,and maybe it's for doctors,
(25:24):
maybe it's a little bit larger.
what's the glow up that you'rewanting to see in the healthcare
and health technology space?
Aditi Joshi (25:31):
So, yeah, in the health technology space, I am
seeing this glow up and I wantmore of this.
Nathan C (25:36):
I like this.
Aditi Joshi (25:36):
There's a lot more clinicians here and they have a
real voice, and there's a lot ofclinician builders, founders
here.
Not just, you know, on the execteam, not just advisors.
There's actual builders andfounders.
That's really important becausefor so long we were told we're
not good at business, we're notgood at speaking on these
topics, and I think we'regetting past that where we don't
(25:57):
actually have to have those.
Skills we can find co-founders,we can find those skills just
like everybody else does, right?
I love that.
I'm seeing that trend.
Nathan C (26:04):
So for those who might be watching the tech glow up who
aren't familiar with healthcaretechnology, I think it might be
shocking.
Honestly.
Oh, sure.
That doctors, yeah.
Haven't always been involved insome of the tech innovation.
A lot Of the tech innovationthat has happened to date.
(26:25):
Yes.
And that a lot of solutions kindof solved technical, physical,
clinical kinds of problems, butweren't necessarily even
including, to your point at thetop Yes.
That people are supposed to beusing the tools Right.
And saving them time.
Aditi Joshi (26:40):
Yeah.
I was shocked too when I foundthis out, but it was like, it's
been a long time that this hasbeen going on.
Nathan C (26:44):
I've also heard, the voice of doctors, the voice of
nurses.
The voice of patients.
I can see the lounge From here.
that is one of the things thatthis event fair, is very good at
centering, like literally givingprime center booth space.
So boosting it everywhere.
Props to HTLH.
Aditi Joshi (26:59):
Yes.
Nathan C (26:59):
Alright, so let's bring it in.
Mm-hmm.
entrepreneur, newly startedcompany.
Six months can be a lot of time,can also be a very little amount
of time at this stage.
What's the glow up that you'relooking for?
to make it our next year in thenext six months.
So first things first.
Yeah.
I've had burnout twice thistime.
(27:19):
I'm not, I'm gonna build.
So that's the first thing I'mdoing.
yes, exactly.
You gotta plan for it.
Aditi Joshi (27:25):
yes, you have to plan for it.
I'm saying this right now, andso when we talk about six
months, I'm not gonna say, allright, I'm gonna have this all
done by six months.
What I'm gonna say is, in thattime, I wanna know how those
problems are really affectingdoctors.
All of my research in there, andstarting that validation.
If it's done, that'd be amazing,but at least getting into that
validation portion.
And hopefully I'll have thattech co-founder and least some
(27:46):
ideas on the tech co-foundersout there who might be
interested in this problem.
Nathan C (27:49):
Hell yeah.
I'm always gonna be excited whensomebody's like, I'm gonna be
doing more research.
I'm hoping to be at this.
I knew that I couldn't start abusiness that was going to burn
me out and support my family inthe way that I wanted to for the
business, and so can't burn out.
Can't burn out, have to havebalance.
(28:10):
Have to be mentally healthy aspart of the business plan.
Like it's in the foundationalvalues for how Awesome Future is
supposed to run.
Yes.
Because how else am I gonnaprotect it as a CEO and as the
only employee right now.
Yes.
Aditi Joshi (28:25):
Yeah.
Nathan C (28:25):
so true.
Aditi Joshi (28:26):
I love that you did that and you put in the business
plan because if you burn out,you can't actually build
anything.
You're not grounded.
You have no energy to do it.
And I know myself, I'll just betoo hard on myself and really
want to do something.
Nathan C (28:36):
Yeah.
But your brain cannot thinkstrategically and creatively if
you're in fight or flight.
Aditi Joshi (28:43):
That's true,
Nathan C (28:44):
When you're in the wrong part of the brain, it's
true.
Like you're physically notcapable.
You can't hustle your waythrough that.
It's like a physical meatbarrier, and I love it.
so Aditi, the theme for healththis year is Heroes and Legends.
I think this is a fantasticopportunity to ask CEOs,
leaders, product founders,innovators, who are those
(29:07):
mentors and heroes thatencouraged you along the way,
Like sometimes it can take justone person believing in you, in
your idea.
In your potential.
So who helped you get to thepoint where you are?
Aditi Joshi (29:20):
And I love this question and there's been so
many people, but I will saythat, what probably some of the
ones I can really think of thatreally.
Help me.
Were the ones that recognizedthat telemedicine is important.
They may not have been intelemedicine, but colleagues who
were like, we want you to be thevoice and we want to make sure
that you actually grow this out.
And I've had multiple ones.
My boss at Jefferson, mycolleague at Jefferson, who also
(29:42):
made sure I had, more,opportunities to write papers
and do research.
I mean, all of that.
Really made me realize that Ican do this.
But I gotta say, you know, andthis is such a cliche answer,
but I remember even when I wrotemy book, like I remember
thinking all of the patientsthat I saw, because I will tell
you I have like memories ofcertain patients and I just was
(30:02):
like, oh my God, I remember howit helped you and I remember
what this did for you, both fromthe emergency department and on
telemedicine visits and reallyall of that.
It's really why I do it, becauseotherwise, I mean, this is a
hard problem.
Nathan C (30:16):
those stories of the people that you were able to
help and learn from, stick withyou no matter what.
Yes.
and how cool that it's like thepeople that you were able to
help and engage on their healthjourneys now coming back as like
advisors and encouragement.
I love that so much.
Aditi Joshi (30:34):
Thank you.
I love that.
Nathan C (30:35):
Yeah.
So on a total tone shift, do youhave any spicy ideas you're
willing to share with us?
Aditi Joshi (30:43):
Absolutely, and I don't know if you know, it's a
spicy, but I'm gonna say that I.
I'm seeing AI everywhere andit's like, honestly, it's lost.
Its meaning.
There's no differentiation.
And so for me, when I'm walkingaround, I'm like, okay, well
you're using AI now I need toknow what you're doing with it,
what kind of AI you're using.
'cause like I'm gonna tell you,I've been talking to people and
I've been trialing things out.
And if your base or back end AIor LLM doesn't have certain
(31:07):
features, it is missing out onsome of the ambient ai.
It is taking things out ofcontext, it's giving wrong
answers.
So just what kind of AI are youusing and then how are you using
it?
Because I don't wanna hear aboutAI anymore, I wanna know what
it's actually doing.
Everybody has ai, so tell mesomething different.
Nathan C (31:22):
Tell us about your outcomes.
Aditi Joshi (31:25):
Yes, yes,
Nathan C (31:26):
please.
I love that.
That's amazing.
Aditi, Nathan, we've got themic.
We've got the opportunity toshare anything you'd like about
Ardexia, what you're looking forin the next few months.
Aditi Joshi (31:41):
I would love to know if anybody is really
looking on how to improve this.
I wanna talk to you.
Not even necessarily for thevalidation or even as a client,
but I wanna hear your stories.
I wanna know what's going on.
'cause really this is theproblem I want to solve.
I wanna make, I wanna make thesetools usable by clinicians and
that hospitals will actuallyadopt them and continue to do
it.
'cause if we don't use'em,they're just gonna go away.
(32:01):
They're just gonna sit thereunused on a shelf and patients
are not gonna get the care thatwe can deliver through
technology.
Nathan C (32:08):
Do you have metrics on.
The cost or the lost value oflike digital transformation
that's unused.
Billions in healthcare.
Aditi Joshi (32:19):
Billions.
Nathan C (32:19):
It's probably trillions.
Aditi Joshi (32:21):
It's 87 billion.
Nathan C (32:22):
It's at least, okay.
Aditi Joshi (32:24):
per year, they've contracted, so you're looking at
not only the investment, but howmuch they're losing in a
hospital by not using and seeingpatients and getting reimbursed
for that.
Care.
Nathan C (32:34):
A five year contract is a five year contract.
Even if the nurses don't touchit in the EHR.
Aditi Joshi (32:38):
That's right.
Ooh.
Right.
I'm gonna actually,
Nathan C (32:41):
a five year contract is a five year contract.
Even if the doctors don't touchit in the ehr.
Aditi Joshi (32:46):
that's true.
And everyone, I'm not gonnathrow nurses under the bus,
doctors and nurses.
it's not even us doing it.
If we, doctors will turn thesetools off if it's not useful.
and you have to actually talk tothem.
And figure out why it's notuseful and then fix it.
Most doctors don't have time.
They're not gonna sit here andjust like try to fix it for you.
They're just gonna stop usingit.
That's actually what happens.
Nathan C (33:04):
Literally turn it off.
This is wasting too much of mytime to learn.
Aditi Joshi (33:07):
Exactly.
Nathan C (33:08):
Oh, I'm so glad I asked that follow up.
Thank you, Aditi.
It has been such a fantasticpleasure to check in and to see
everything that you're doing atArdexia.
The research foundation, thatdesire to drive outcomes and
actually make a difference andhelp your peers also make more
(33:28):
of a difference, right?
With the tools that we'vealready bought, is such an
incredible mission.
I hope we can have a follow upin a year so we can hear more.
Yes.
About everything you've beenbuilding.
Aditi Joshi (33:41):
I would always love to follow up with you, so let's
do it.
Thank you for having me, Nathan.
Nathan C (33:44):
Yes.
And now we gotta clap it out.
Okay.
1, 2, 3.
Aditi Joshi (33:49):
Thank you.
Thank you.
Have fun.
everything that we say as part of answers is
(00:02):
always referenced.
So there's citations toeverything.
And so you don't actually haveto trust AI at all to get value.
Use Open Evidence because youcan always verify, everything.
And so our motto, here, istrust, but verify.
And that's really central toOpen Evidence.
Nathan C (00:16):
So, you ready?
1, 2, 3.
Hello and welcome to the HLTHTech Glow Up.
I'm Nathan C and today I'mtalking with Zachary Ziegler,
co-founder of Open Evidence.
Zach, it's so great to meet you.
Thanks for joining me on theHLTH Tech Glow Up.
Hello.
Amazing.
(00:36):
So, to get started, can youintroduce yourself and the work
that you're doing at OpenEvidence?
Zachary Ziegler (00:42):
Yeah.
So I'm Zach.
I'm the co-founder and CTO ofOpen Evidence, we essentially
make, Chat GPT for doctors.
We become the fastest growing,most rapidly adopted, AI tool
used by clinicians.
we're now used by over, 40% ofpracticing clinicians with the
average user using us, everyday.
Okay.
my background is technical.
(01:03):
I'm, I'm an AI person.
Mm-hmm.
I come from a PhD program atHarvard, where I was working in
the pre-chat GPT days on,language models and generative
modeling and all that stuff.
and yeah, I got reallyinterested in how do we make
these models do somethingactually useful?
How do we make these models likeactually impact the world in a
meaningful way?
and yeah, ended up, you know,here we are.
Nathan C (01:24):
Were you always interested in healthcare as an
application for large languagemodels, or did that focus come
out of the research that you didin building, the idea?
Zachary Ziegler (01:39):
Yeah, so ultimately what motivates me is
just making useful stuff.
That's always been just thething to just really make things
that people love and people use.
And what struck me early on,myself and my co-founder Daniel,
was that, healthcare sits inthis space that is, In so much
red tape and bureaucracy.
when we were getting startedwith this, it was one of these
last very obviously yellow taxicab era style, industries, Where
(02:03):
even as consumers, it was wildto us that if you want to know
what is the science actually thebreast resource is, WebMD.
Mm-hmm.
Which is crazy because it isliterally a meme.
right.
That you go to MD and you ask,but you have, and it'll tell you
you have cancer.
Yeah.
and, and the, what the, theshame is, is that there's so
much that we know as a species.
I don't think people appreciatehow much medical knowledge
exists and how much researchexists.
(02:25):
there's 40 million papers.
There's.
10 to 20,000 new or updatedpapers every single day.
It's an enormous amount ofliterature.
Nathan C (02:32):
almost like a YouTube.
I mean, that's a similarcontent.
Sure.
Fee.
Yeah, that's right.
Zachary Ziegler (02:36):
huge amount of, context area, and yet there's no
real ability to access thatknowledge.
And so we made Open Evidence tobe kind of a bridge between
people who have needs, whetherthat's, originally kind of when
we were.
Considering this, for WebMD kindof consumer stuff, but very
quickly, you know, really,focused on the physician side.
and providers, to bridge the gapbetween providers who need
(02:57):
access to the, best, informationand the best care.
And that information that reallydoes exist in the home.
That's amazing.
Nathan C (03:05):
Could you, for the sake of those who maybe aren't
in the health tech space, talkabout your data sources and, how
you collect the research and,what is it like for a doctor to
use, Open Evidence?
Zachary Ziegler (03:20):
Yeah.
So, we pull data from a bunch ofdifferent sources and we do it
in a bunch of different ways.
Probably the most important datathat we work with is our first
party content partnerships.
we have, partnerships with, theNew England Journal Medicine
jama, and a whole bunch of,societies as well.
these are the absolute top ofthe top, the biggest gold
standard for, clinicalinformation.
This is where the.
Best phase three clinical trialsare published, and really the
(03:43):
most kind of world changing,aspects of, of medical knowledge
exists.
So it's really important that wehave, those deep partnerships.
we're able to kind of show anduse figures, especially in
multimedia from those which arereally cool.
and we're working on kind offurther collaboration with those
as well.
Nathan C (03:59):
That's like dimensions that audio or like other modes.
Might miss out on Yeah.
like, speaker's, slides and somerecorded CTA thing or something.
amazing.
So, my kids are like ultimate AIskeptics.
Yeah.
And, I've even heard at theshow, right, people talking
about, hallucinations are real.
(04:20):
I'm sure you've addressed it,but I'm hoping you can talk to,
like what are the risk factorsfor being an AI layer for like
medical research andinformation, especially like
when you're working with doctorsand advising or, you know, kind
of.
Affecting how they're makingdecisions about care.
Zachary Ziegler (04:39):
so the way that we approach this problem is we
focus on search essentially.
Is the answer, right?
There's traditional approaches,chat BT might imagine, right?
Which is like big black box,throw some questions and just
like hope that you get goodanswers.
We take a very differentapproach, which is essentially
the bottom up to that top down.
So we, we really, at the end ofthe day, we do search.
That's what we do.
(04:59):
And so what that means is whenusers have questions or clinical
cases, we will find the exactright sentence, paragraph, we
see our job as really beingsearched, just surfacing those
pieces, to humans.
And then largely what we use,kind of what people today think
about AI for it is, makingreally great search and then
also providing a layer offluency and conversation on that
(05:20):
just for a kind of convenientexperience.
And so what that means is thateverything is from the bottom
up.
Everything is about, You know,true what humans have said, what
humans have written, what humanshave published and gone through
peer review.
And then also the side effect ofthat, which is just as
important, is that everythingthat we say as part of answers
is always referenced.
So there's citations toeverything.
And so you don't actually haveto trust AI at all to get value.
(05:43):
Use Open Evidence because youcan always verify, everything.
And so our motto, here, istrust, but verify.
And that's really central toOpen Evidence.
Nathan C (05:51):
Do on the platform side, you potentially have, this
is like just riffing.
ability to understand howfrequently doctors are actually
clicking in to those references.
Is that something you're able totalk to at all?
Zachary Ziegler (06:07):
don't know the exact number, but it's, it.
It is really quite frequent.
it's, you know, it's, it'sreally important, right?
if you're a doctor seeing apatient, you are responsible for
making the decision.
There's nobody else.
And so Open Evidence is a placethat people go because it's
just, one layer of support.
That's a really common kind ofuse case.
but at the end of the day, thestakes are high.
There's someone there insomeone's life, right?
In principle, in the worst case.
(06:28):
And so, having that ability tolook through and double check
and go to the references andsee, exactly what the, original
source material said.
I can't imagine practicing usingany kind of AI tools without
that foundational support.
Nathan C (06:43):
The, I would say that like one of the themes I've been
seeing at health, like overallYeah.
Has been like ai, but there'sstill a human.
Totally.
And in many cases that's part oflike the rebuttal page for an AI
product.
Yeah.
Right.
Like, but there's a human inline or we have this person, or
(07:05):
there's a trans.
Later.
And what, what I kind of findreally elegant about what you're
describing is that the humaninvolved is the customer, is the
doctor doing the search?
And so it's built in to the workflow that the human is always
gonna be at the front.
(07:25):
Yeah, because you're notnecessarily like asking for a
diagnosis, you're not asking,right.
Like you're asking for theresearch.
You're asking to get right tothe specific thing that I really
want to address.
First and then that ability tohave a conversational.
interface to the research, forsomebody who can make a
decision.
Zachary Ziegler (07:45):
Yeah.
Nathan C (07:46):
And, I'm sure people much, I'm not even gonna get
into the, like, models canhallucinate even if they're day
like.
there's something, but I lovethat there's a safety layer and
just like an elegant, asimplicity of the technology
That align very well, in thismodel.
So it's,
Zachary Ziegler (08:02):
very cool.
There are, questions, whateverconcerns when AI is framed in a
way that is kind of aboutreplacing humans, right?
Mm-hmm.
And that's when you startgetting into like, okay, we're
gonna start with some human inthe loop thing.
Mm-hmm.
And eventually we're gonnaremove that and replace that
human with position.
That's really not at all how wethink about this, right?
We really think about this AI asjust a tool that is.
(08:25):
Supportive of physicians.
we don't think about it in termsof replacing.
we also don't even think aboutit truly in terms of even saving
time.
There's, another common thing islike, AI is gonna save time for
physicians.
And the reality is that's, thenwhat happens is immediately,
health systems just startcompressing schedules and giving
more and more, patients to eachphysician.
So what we think about at theend of the day, or maybe they
play wordle well, there's noguarantee that it's.
(08:47):
Go into efficiency or, physicianlines are hard enough.
Yeah.
You don't, these, for-profithospital, these are efficiency
machines.
They're just going to, anyamount of save time really just
increases, the amount ofpatients people have to see.
So, what we care about and whatwe focus on truly with Open
Evidence.
Is, how do we make doctor liveseasier?
How do we make it just notfaster, but just truly easier to
do their job?
Nathan C (09:07):
There's a little bit that you hinted at about like
leveraging information to combatsome of the challenges of the
weird.
Investment structure inhealthcare, that I'm not even
gonna touch, but is like supercool, like some very interesting
ideas.
so thank you for that, Zachary.
(09:28):
This is like, such a cooltechnology and to have 40% of
practitioners in a daily,actually, how long did it take
you to get to daily use, like.
Zachary Ziegler (09:38):
Yeah, well we, so we started about two years
ago.
Mm-hmm.
Releasing Open Evidence.
But it's really just in the lastyear that we have absolutely
exploded and taken off.
We've been growing about 30 to40% month over month.
so, you know, in our early daysthat was, small numbers.
But the nature of exponentialgrowth is all of a sudden that
gets very big, very fast.
we're adding 60 to 70,000clinicians, per month at this
(09:58):
point.
and it's fantastic.
we, you know, we're thrilled tobe making a difference and to be
making, really fantastic tools.
Nathan C (10:05):
60 to 70,000 a month gets.
To millions really fast.
Yes.
That's cool.
amazing.
so let's, let's go a little bitbigger.
let's look at the industry.
Look at why we're here.
the podcast we're on right nowis the HLTH Tech Glow Up.
A Glow Up is a notable rebirth,a transformation looking at the
(10:26):
healthcare industry, like you'realready solving some of these
core problems and like workingon some of these hot issues.
I'm.
Curious what's, what's theperspective, what's the goals
that you have, for healthcare,for practitioners?
what's the big audacious goals,that you have for healthcare and
health tech, in the next sixmonths to a year?
Zachary Ziegler (10:44):
Yeah.
Well, I think it's this reallyinteresting moment where it
feels like kind of all the dusthas been kicked up and there's
questions around like, how todescribe, play into things,
right?
How do, clinical copilots playinto things?
Does integration matter?
Does integration not matter?
Right.
And so I think, you know whatI'm, what I'm really intrigued
by is like where, you know, howdoes this all land?
Kind of like what is, what, asthis kind of normalizes into,
(11:07):
into physician flows, like, youknow, healthcare is an
enormously varied, so.
Base, right?
It's not just one thing.
Practice looks like enormouslydifferent, in many different
situations.
And so I think there's, it's areally exciting moment where
it's never been easier to buildAI tools, right, or to build,
any tools at all with just howfast it is, increasingly to
(11:28):
build products.
and so I think it's a reallyinteresting opportunity to, run
as fast as we can at buildingthe most useful tools for
physicians, to make stuff thatreally find the places that can
help every physician.
I'm especially reallyinterested, for our part in, you
know, how far can we push thesemodels?
How far can we push medicalreasoning?
How far can we push, medicalintelligence?
Can, you know, is there anythinglike that really starts to
(11:49):
approach medical superintelligence that we can, that
we can build with a con with.
The, with the, you know,foundation of the literature and
guidelines and practiceinformation.
but as we especially level upreasoning and, and, and those
sorts of capabilities.
So that's what I'm reallyexcited about.
those are, we're working on someof that stuff and we'll see,
see, can, is
Nathan C (12:05):
there, not to pin you down to any of these specific
goals, but for medical superintelligence, what would be the
first problem you would gosolve?
Zachary Ziegler (12:16):
Well, the reality is I think it's a big
spectrum, right?
There's Open Evidence like issuper intelligent from a like.
in specific instances, right?
The ability to, have 40 millionpapers condensed into one tool
that you can kind of query fromand get access to is something
that,
Nathan C (12:32):
an executive summary is pretty good.
Zachary Ziegler (12:34):
can't do that, right?
So there is, there is somethingthat a lot special about that.
But there are also plenty ofaspects that I don't think we're
gonna recreate for a very longtime, right?
I think human intuition,physician intuition, and
experience is so important andso critical.
I think we'll figure out how tomesh, continue to mesh those
pieces.
Nathan C (12:50):
Yeah.
that's gonna be my new ai.
Amazing.
you kind of actually answered, alittle bit about the Glow Up for
Open Evidence.
You teased this question thatlike I have to come back to, are
integrations important or arethey not?
do you have an opinion on that?
Zachary Ziegler (13:09):
I think they're okay.
I don't think they'reexistential, I don't think
they're critical.
You know what, when I talk toclinicians, what I hear is the
core value, the core thing thatis really important is being
able to just get fast answers,fast, trustworthy answers to
questions, right?
The idea that you can pull outyour phone when you're standing
outside the patient room, ask areally challenging but important
(13:31):
question and get an answer rightaway, that is easy.
It's that ease of use.
I think that's the thing that wealways push for ease of use and
low barriers.
I often cite ease ofintegrations as the fastest path
Yeah.
To ease of use.
Yeah.
And like meeting customers wherethey are.
Yeah.
but if you're in a world whereyou can build AI tools quickly
(13:56):
and a doctor actually doesn'tmind pulling out their phone to
like get the answer that theyneed in the moment, and maybe
that's their preference.
change it if it's not, if it'snot broken in healthcare
especially, right?
Like physicians are essentiallyjust like.
they are force fed EHRs, andit's like, you know, one of the
most like interesting, wellcited facts that I keep coming
(14:18):
back to, and it's just like I,it keeps bo bopping around in my
head is that like EHRsthemselves are cited as like one
of the top three causes ofburnout by physicians, right?
I mean, one.
Crazy profession to live inwhere the technology that your
administration is often forcingon you is the very thing that is
like, I have to click all thesebuttons.
It's a huge pain in the ass.
Why do I have to do this?
(14:38):
and so for physiciansspecifically, I don't think they
all.
Love their existing EHRs, andI'm not sure they're like, boy,
what I really want is more, eh,HR.
You know what I mean?
Yeah.
Nathan C (14:48):
EHRs are the TPS reports.
Health tech is what I've justlearned there.
Zach, you're pushing on some ofthe conventional wisdom that I
like to talk about in a coupledifferent areas.
Yeah.
I'm trying not to be upset aboutit.
Let's jump to the next thematicquestion as a diversion.
(15:09):
The theme for the show this yearis Heroes and Legends, and I'm
using it as an opportunity toask people about the mentors,
heroes and others, both inhealthcare and in innovation.
Sometimes just having one personbelieve in you and say, keep
going, can, like, havetransformational effects.
(15:31):
And so I'm using thisopportunity to try to get to
those stories.
Are there people who, ororganiza, you know, heroes,
legends in any way that haveinspired you on your journey as
an innovator?
Zachary Ziegler (15:45):
well not, not, maybe not quite mentor
specifically because I never metthis person.
but in terms of, A guidingfigure.
Yeah.
I think a lot about, Steve Jobs.
Yeah.
and specifically in thehealthcare sense.
Oh.
Because, do you know what thetechnology that was the fastest
adoption technology before OpenEvidence was among physicians?
Nathan C (16:06):
based on the context, my guess is gonna be the Apple
Watch iPhone.
Okay.
Zachary Ziegler (16:12):
that was, you know, like we're in now with
this AI movement where there's,so much, happening so quickly.
Right.
In so much, like I said, up inthe air and changing.
That was a previous periodwhere, there was this.
introduction of new technology.
I was just talking earlier withsome positions that were
talking, when they got theirfirst iPhone.
First it was an iPod Touch andthen an iPhone, and what a
change that was to, level upfrom textbooks to all of a
(16:35):
sudden, still set of content,but just have that right there
in your pocket.
and so, you know, that's a.
Cool.
kind of like precursor in a lotof ways that mirrors a lot of
this, but, you know, and thenjust as an individual, right?
Like Steve Jobs is absolutelyincredible and I think he has
some of the best, kind ofphilosophies for building a
company, for innovating.
And, and, yeah, he, he'sabsolutely.
(16:57):
Inspirational figure for, forhow to build things for real and
make things in practice.
Nathan C (17:01):
I love that there's like a, I love Steve Jobs as a
hero there because there's thislike uncompromising quality and
focus on design.
Yeah.
So, last question, and it'stotally optional.
What year was that adoption?
I dunno.
Dr.
Lee.
We are like, one minute I have
Dr. Lee Glasser (17:20):
to go on the
Nathan C (17:20):
call.
Dr. Lee Glasser (17:20):
I'm er, I was friends with Danny.
Okay.
Yeah.
And I'd love to talk you, it's aformer Chief Medical CMS and I
know a lot of work.
Amazing.
And reasoning and writing.
Yeah.
Yeah.
How to educate the nextgeneration of yeah.
Talked to George Daley about, Idunno if you know George?
No.
Harvard Medical School.
Oh, okay.
Yeah.
So your team has my number.
(17:42):
Okay,
Zachary Ziegler (17:42):
Yeah.
Dr. Lee Glasser (17:43):
Okay.
Zachary Ziegler (17:43):
Awesome.
Dr. Lee Glasser (17:43):
heard you spent some time with Danny.
Zachary Ziegler (17:45):
yeah, my co-founder for Luxury.
He became your friend.
He was special person.
Yeah.
Nathan C (17:51):
Smartest
Zachary Ziegler (17:51):
man I've ever met.
Hey you.
Nathan C (17:52):
Hell yeah.
Harvard Connections live on theGlow Up last question, Zach, and
it's totally optional.
Do you have a spicy healthcarehot take?
Zachary Ziegler (18:06):
I don't know actually if this is a hot take.
But I think that AI is onlygoing to extremely, positively
impact all of our lives.
there's so much, concern andfear, right?
And anxiety around ai.
Is it taking people's jobs?
is it leading to ai slop, If yougo on the internet, it's almost
exclusively negative, right?
Open Evidence shows that thereare ways for it to literally
(18:28):
save lives, right?
for it to impact the world at avery large scale in a way that's
extremely positive.
It's very easy to be negative onstuff and it's very easy to
point out problems.
I think we'll look back a year,two years, three years, and
certainly much farther than thatand see this as a really
important step function for thewhole world.
I see that in the clinicianspace for Open Evidence.
(18:49):
I see that as an engineer incoding tools.
and I think as this percolatesfarther through to society and
people start.
Seeing the reality every day aspart of their jobs.
It's going to be very clear justhow positively beneficial AI can
be for the whole world.
Nathan C (19:04):
I'll take it.
some of that sentiment remindsme of some things that, Alvin
Wang Graylin, talks about.
I don't know if you're familiarwith Alvin, he's a, former
leader at HTC, but very much,interested in AI in this
direction.
Zach.
It's been fantastic, to chatwith you.
Thank you so much for sharingsome of your very busy day.
(19:26):
Yeah.
here at HLTH and, you know, justfantastic work.
I think, that optimism of howpowerful AI can be has gotta be
partly a product of.
How incredibly successful you'vebeen able to be in the last four
years, building with it.
Right.
And while many of us are stilltrying to find our paths, you're
(19:46):
here trailblazing, with outcomesand like centering doctors in a
way that a lot of folks seem tohave a hard time doing.
So Bravo.
Well thank you and thanks forjoining us on the Health Tech
Glow Up.
Thanks for having me.
Amazing.
We got one last thing.
We're just gonna clap it out.
Okay.
1, 2, 3.
Amazing.
(20:08):
So one, two.
Awesome.
Hello and welcome to the HealthTech Glow Up.
I'm Nathan C, and today I amtalking with Aditi Joshi of
Ardexia.
Aditi it is so good to see you.
Thanks for joining me on theHealth Tech Glow Up.
Aditi Joshi (20:24):
Thank you.
Thanks for having me.
And hello everybody.
Nathan C (20:27):
Amazing.
Can you introduce yourself andthe work that you do at Ardexia?
Aditi Joshi (20:32):
Yes.
Thank you for calling me anicon.
I'm gonna live off that now, but
Nathan C (20:35):
yeah,
Aditi Joshi (20:35):
so this is a new company for me, and we've known
each other for a few years, weknow what we want to do for
healthcare, but it's just nothappening.
So looking back at like whateverything I've built and I
realized that it's.
We've got great technology.
People really want to helphealthcare.
We have leadership and laws andeverybody's involved, but we
still haven't been able toreally get doctors who want to
(20:56):
use it successfully.
There are health systems, thereare government programs, there
are clinics.
People are sitting on technologythat isn't being used.
And so I thought to myself overthese last 12 years.
What has worked, what have Iseen actually work to get
doctors to actually want to useit.
And that's what we're doing andwe're fixing.
Nathan C (21:16):
Are you able to share what it is you've seen that
doctors actually want to and douse?
Aditi Joshi (21:24):
Yes, I will say that.
the biggest problem is thatpeople don't really understand
how doctors work.
The biggest take is that wedon't really have bosses.
We have people who haveoversight, but once you're at
the standard of care, we don'treally have bosses.
We are able to see our patientsand decide what we wanna do.
We have to do the right thingfor them, but that's it.
(21:44):
So you can't actually go into ahealth system.
You can't be like, Heyeverybody, you've gotta use this
tool.
If there's a tool that alreadyworks and is great for patient
care, you cannot force us to doit.
It's just not happening.
You have to look at what are theactual pain points?
What do we want better forpatient care?
What is the actual behavior andpsychology of the doctors at
that practice that's stoppingthem from using it?
(22:05):
What are the real pain points?
Who's the leadership?
You gotta think about all ofthose things.
Nathan C (22:10):
My suspicion is like, just for the sake of example,
right?
Like a podiatrist and a oncologydoctor are gonna have incredibly
different drivers, even thoughthey might sort of have some of
the same credentials or youcould put the same labels on
them.
Aditi Joshi (22:28):
Yes.
Nathan C (22:29):
so what's your approach for helping
technologies better understandand activate doctors?
Aditi Joshi (22:39):
So I put it out, I looked at my playbooks and it
just basically.
Put it out there, and I figured,all right, these are the steps
that you need to take.
So the first thing we have to dois actually validate it.
And I'll tell you, Nathan, Iknow it works.
I have done it multiple times,but I need to make sure that it
works in this context.
And then once I do it, I'm gonnabuild an app around it.
So looking for any techco-founders, if you know anybody
(22:59):
who might be interested.
Nathan C (23:00):
interesting.
Have, this is totally like,curiosity around innovators and
the choices they make in,excited circles.
There's a lot of people that sayyou don't need a technical
co-founder anymore because youcan prototype and.
Create a number of like proof ofvalue apps with AI code
(23:22):
assistance.
what's your thoughts as afounder?
Aditi Joshi (23:25):
I'll say that AI has come really far and it's
actually really exciting whatyou can do with it.
But I will fully admit this.
I have taken on a veryambitious, complicated problem,
and so I did actually trycreating an.
App using the playbook that Idid.
it does part of it, but it doesnot get everything that I want.
And so I know that I'm gonnaneed somebody who has a little
bit more experience to makeexactly what I'm looking for to
(23:46):
do.
Nathan C (23:47):
Yeah.
along with that intuition andthat experience.
Right.
Like back to the, the top, like,I've done it before.
I've seen what works.
I'm, I'm curious, you're kind ofmultihyphenate.
You've got these many strengths.
what was that, origin story,that moment that inspired you to
kind of take this innovationpath when you have so many tools
at your disposal?
Aditi Joshi (24:08):
Oh, yes.
So I'll say that in general.
Emergency medicine, we tend tobe innovative because we have to
think on our feed.
We have to really make surethat.
We're going in the rightdirection, and if it's not, we
gotta change paths.
But really my story was I gotburnout and I really could not
work in the emergency room atthe level that I was doing or
the amount of time that I wasspending there.
(24:29):
And so I was looking for otherthings and I applied for a
telemedicine company and I justreally loved what they were
trying to do.
And I will tell everybody this,You cannot just try to escape
your burnout by going into afield like this unless you
actually love it.
I actually loved it.
I found it useful.
I understand how we improveaccess to care.
(24:49):
I saw patients, I have multiplestories where I helped them and
really understood what it's likefor patients at home, which I
don't see in the hospitalsetting.
And it really gave me anunderstanding of what technology
can really do to help people intheir homes.
Nathan C (25:02):
So let's look at the conference and the setting that
we're in, sort of dive in, toHTLH itself.
I use the idea of a glow up or anoticeable transformation or a
rebirth.
As a way to talk about goals.
Mm-hmm.
and how we grow into the future.
Thinking at the industry level,and maybe it's for doctors,
(25:24):
maybe it's a little bit larger.
what's the glow up that you'rewanting to see in the healthcare
and health technology space?
Aditi Joshi (25:31):
So, yeah, in the health technology space, I am
seeing this glow up and I wantmore of this.
Nathan C (25:36):
I like this.
Aditi Joshi (25:36):
There's a lot more clinicians here and they have a
real voice, and there's a lot ofclinician builders, founders
here.
Not just, you know, on the execteam, not just advisors.
There's actual builders andfounders.
That's really important becausefor so long we were told we're
not good at business, we're notgood at speaking on these
topics, and I think we'regetting past that where we don't
(25:57):
actually have to have those.
Skills we can find co-founders,we can find those skills just
like everybody else does, right?
I love that.
I'm seeing that trend.
Nathan C (26:04):
So for those who might be watching the tech glow up who
aren't familiar with healthcaretechnology, I think it might be
shocking.
Honestly.
Oh, sure.
That doctors, yeah.
Haven't always been involved insome of the tech innovation.
A lot Of the tech innovationthat has happened to date.
(26:25):
Yes.
And that a lot of solutions kindof solved technical, physical,
clinical kinds of problems, butweren't necessarily even
including, to your point at thetop Yes.
That people are supposed to beusing the tools Right.
And saving them time.
Aditi Joshi (26:40):
Yeah.
I was shocked too when I foundthis out, but it was like, it's
been a long time that this hasbeen going on.
Nathan C (26:44):
I've also heard, the voice of doctors, the voice of
nurses.
The voice of patients.
I can see the lounge From here.
that is one of the things thatthis event fair, is very good at
centering, like literally givingprime center booth space.
So boosting it everywhere.
Props to HTLH.
Aditi Joshi (26:59):
Yes.
Nathan C (26:59):
Alright, so let's bring it in.
Mm-hmm.
entrepreneur, newly startedcompany.
Six months can be a lot of time,can also be a very little amount
of time at this stage.
What's the glow up that you'relooking for?
to make it our next year in thenext six months.
So first things first.
Yeah.
I've had burnout twice thistime.
(27:19):
I'm not, I'm gonna build.
So that's the first thing I'mdoing.
yes, exactly.
You gotta plan for it.
Aditi Joshi (27:25):
yes, you have to plan for it.
I'm saying this right now, andso when we talk about six
months, I'm not gonna say, allright, I'm gonna have this all
done by six months.
What I'm gonna say is, in thattime, I wanna know how those
problems are really affectingdoctors.
All of my research in there, andstarting that validation.
If it's done, that'd be amazing,but at least getting into that
validation portion.
And hopefully I'll have thattech co-founder and least some
(27:46):
ideas on the tech co-foundersout there who might be
interested in this problem.
Nathan C (27:49):
Hell yeah.
I'm always gonna be excited whensomebody's like, I'm gonna be
doing more research.
I'm hoping to be at this.
I knew that I couldn't start abusiness that was going to burn
me out and support my family inthe way that I wanted to for the
business, and so can't burn out.
Can't burn out, have to havebalance.
(28:10):
Have to be mentally healthy aspart of the business plan.
Like it's in the foundationalvalues for how Awesome Future is
supposed to run.
Yes.
Because how else am I gonnaprotect it as a CEO and as the
only employee right now.
Yes.
Aditi Joshi (28:25):
Yeah.
Nathan C (28:25):
so true.
Aditi Joshi (28:26):
I love that you did that and you put in the business
plan because if you burn out,you can't actually build
anything.
You're not grounded.
You have no energy to do it.
And I know myself, I'll just betoo hard on myself and really
want to do something.
Nathan C (28:36):
Yeah.
But your brain cannot thinkstrategically and creatively if
you're in fight or flight.
Aditi Joshi (28:43):
That's true,
Nathan C (28:44):
When you're in the wrong part of the brain, it's
true.
Like you're physically notcapable.
You can't hustle your waythrough that.
It's like a physical meatbarrier, and I love it.
so Aditi, the theme for healththis year is Heroes and Legends.
I think this is a fantasticopportunity to ask CEOs,
leaders, product founders,innovators, who are those
(29:07):
mentors and heroes thatencouraged you along the way,
Like sometimes it can take justone person believing in you, in
your idea.
In your potential.
So who helped you get to thepoint where you are?
Aditi Joshi (29:20):
And I love this question and there's been so
many people, but I will saythat, what probably some of the
ones I can really think of thatreally.
Help me.
Were the ones that recognizedthat telemedicine is important.
They may not have been intelemedicine, but colleagues who
were like, we want you to be thevoice and we want to make sure
that you actually grow this out.
And I've had multiple ones.
My boss at Jefferson, mycolleague at Jefferson, who also
(29:42):
made sure I had, more,opportunities to write papers
and do research.
I mean, all of that.
Really made me realize that Ican do this.
But I gotta say, you know, andthis is such a cliche answer,
but I remember even when I wrotemy book, like I remember
thinking all of the patientsthat I saw, because I will tell
you I have like memories ofcertain patients and I just was
(30:02):
like, oh my God, I remember howit helped you and I remember
what this did for you, both fromthe emergency department and on
telemedicine visits and reallyall of that.
It's really why I do it, becauseotherwise, I mean, this is a
hard problem.
Nathan C (30:16):
those stories of the people that you were able to
help and learn from, stick withyou no matter what.
Yes.
and how cool that it's like thepeople that you were able to
help and engage on their healthjourneys now coming back as like
advisors and encouragement.
I love that so much.
Aditi Joshi (30:34):
Thank you.
I love that.
Nathan C (30:35):
Yeah.
So on a total tone shift, do youhave any spicy ideas you're
willing to share with us?
Aditi Joshi (30:43):
Absolutely, and I don't know if you know, it's a
spicy, but I'm gonna say that I.
I'm seeing AI everywhere andit's like, honestly, it's lost.
Its meaning.
There's no differentiation.
And so for me, when I'm walkingaround, I'm like, okay, well
you're using AI now I need toknow what you're doing with it,
what kind of AI you're using.
'cause like I'm gonna tell you,I've been talking to people and
I've been trialing things out.
And if your base or back end AIor LLM doesn't have certain
(31:07):
features, it is missing out onsome of the ambient ai.
It is taking things out ofcontext, it's giving wrong
answers.
So just what kind of AI are youusing and then how are you using
it?
Because I don't wanna hear aboutAI anymore, I wanna know what
it's actually doing.
Everybody has ai, so tell mesomething different.
Nathan C (31:22):
Tell us about your outcomes.
Aditi Joshi (31:25):
Yes, yes,
Nathan C (31:26):
please.
I love that.
That's amazing.
Aditi, Nathan, we've got themic.
We've got the opportunity toshare anything you'd like about
Ardexia, what you're looking forin the next few months.
Aditi Joshi (31:41):
I would love to know if anybody is really
looking on how to improve this.
I wanna talk to you.
Not even necessarily for thevalidation or even as a client,
but I wanna hear your stories.
I wanna know what's going on.
'cause really this is theproblem I want to solve.
I wanna make, I wanna make thesetools usable by clinicians and
that hospitals will actuallyadopt them and continue to do
it.
'cause if we don't use'em,they're just gonna go away.
(32:01):
They're just gonna sit thereunused on a shelf and patients
are not gonna get the care thatwe can deliver through
technology.
Nathan C (32:08):
Do you have metrics on.
The cost or the lost value oflike digital transformation
that's unused.
Billions in healthcare.
Aditi Joshi (32:19):
Billions.
Nathan C (32:19):
It's probably trillions.
Aditi Joshi (32:21):
It's 87 billion.
Nathan C (32:22):
It's at least, okay.
Aditi Joshi (32:24):
per year, they've contracted, so you're looking at
not only the investment, but howmuch they're losing in a
hospital by not using and seeingpatients and getting reimbursed
for that.
Care.
Nathan C (32:34):
A five year contract is a five year contract.
Even if the nurses don't touchit in the EHR.
Aditi Joshi (32:38):
That's right.
Ooh.
Right.
I'm gonna actually,
Nathan C (32:41):
a five year contract is a five year contract.
Even if the doctors don't touchit in the ehr.
Aditi Joshi (32:46):
that's true.
And everyone, I'm not gonnathrow nurses under the bus,
doctors and nurses.
it's not even us doing it.
If we, doctors will turn thesetools off if it's not useful.
and you have to actually talk tothem.
And figure out why it's notuseful and then fix it.
Most doctors don't have time.
They're not gonna sit here andjust like try to fix it for you.
They're just gonna stop usingit.
That's actually what happens.
Nathan C (33:04):
Literally turn it off.
This is wasting too much of mytime to learn.
Aditi Joshi (33:07):
Exactly.
Nathan C (33:08):
Oh, I'm so glad I asked that follow up.
Thank you, Aditi.
It has been such a fantasticpleasure to check in and to see
everything that you're doing atArdexia.
The research foundation, thatdesire to drive outcomes and
actually make a difference andhelp your peers also make more
(33:28):
of a difference, right?
With the tools that we'vealready bought, is such an
incredible mission.
I hope we can have a follow upin a year so we can hear more.
Yes.
About everything you've beenbuilding.
Aditi Joshi (33:41):
I would always love to follow up with you, so let's
do it.
Thank you for having me, Nathan.
Nathan C (33:44):
Yes.
And now we gotta clap it out.
Okay.
1, 2, 3.
Aditi Joshi (33:49):
Thank you.
Thank you.
Have fun.
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The Burden
The Burden is a documentary series that takes listeners into the hidden places where justice is done (and undone). It dives deep into the lives of heroes and villains. And it focuses a spotlight on those who triumph even when the odds are against them. Season 5 - The Burden: Death & Deceit in Alliance On April Fools Day 1999, 26-year-old Yvonne Layne was found murdered in her Alliance, Ohio home. David Thorne, her ex-boyfriend and father of one of her children, was instantly a suspect. Another young man admitted to the murder, and David breathed a sigh of relief, until the confessed murderer fingered David; “He paid me to do it.” David was sentenced to life without parole. Two decades later, Pulitzer winner and podcast host, Maggie Freleng (Bone Valley Season 3: Graves County, Wrongful Conviction, Suave) launched a “live” investigation into David's conviction alongside Jason Baldwin (himself wrongfully convicted as a member of the West Memphis Three). Maggie had come to believe that the entire investigation of David was botched by the tiny local police department, or worse, covered up the real killer. Was Maggie correct? Was David’s claim of innocence credible? In Death and Deceit in Alliance, Maggie recounts the case that launched her career, and ultimately, “broke” her.” The results will shock the listener and reduce Maggie to tears and self-doubt. This is not your typical wrongful conviction story. In fact, it turns the genre on its head. It asks the question: What if our champions are foolish? Season 4 - The Burden: Get the Money and Run “Trying to murder my father, this was the thing that put me on the path.” That’s Joe Loya and that path was bank robbery. Bank, bank, bank, bank, bank. In season 4 of The Burden: Get the Money and Run, we hear from Joe who was once the most prolific bank robber in Southern California, and beyond. He used disguises, body doubles, proxies. He leaped over counters, grabbed the money and ran. Even as the FBI was closing in. It was a showdown between a daring bank robber, and a patient FBI agent. Joe was no ordinary bank robber. He was bright, articulate, charismatic, and driven by a dark rage that he summoned up at will. In seven episodes, Joe tells all: the what, the how… and the why. Including why he tried to murder his father. Season 3 - The Burden: Avenger Miriam Lewin is one of Argentina’s leading journalists today. At 19 years old, she was kidnapped off the streets of Buenos Aires for her political activism and thrown into a concentration camp. Thousands of her fellow inmates were executed, tossed alive from a cargo plane into the ocean. Miriam, along with a handful of others, will survive the camp. Then as a journalist, she will wage a decades long campaign to bring her tormentors to justice. Avenger is about one woman’s triumphant battle against unbelievable odds to survive torture, claim justice for the crimes done against her and others like her, and change the future of her country. Season 2 - The Burden: Empire on Blood Empire on Blood is set in the Bronx, NY, in the early 90s, when two young drug dealers ruled an intersection known as “The Corner on Blood.” The boss, Calvin Buari, lived large. He and a protege swore they would build an empire on blood. Then the relationship frayed and the protege accused Calvin of a double homicide which he claimed he didn’t do. But did he? Award-winning journalist Steve Fishman spent seven years to answer that question. This is the story of one man’s last chance to overturn his life sentence. He may prevail, but someone’s gotta pay. The Burden: Empire on Blood is the director’s cut of the true crime classic which reached #1 on the charts when it was first released half a dozen years ago. Season 1 - The Burden In the 1990s, Detective Louis N. Scarcella was legendary. In a city overrun by violent crime, he cracked the toughest cases and put away the worst criminals. “The Hulk” was his nickname. Then the story changed. Scarcella ran into a group of convicted murderers who all say they are innocent. They turned themselves into jailhouse-lawyers and in prison founded a lway firm. When they realized Scarcella helped put many of them away, they set their sights on taking him down. And with the help of a NY Times reporter they have a chance. For years, Scarcella insisted he did nothing wrong. But that’s all he’d say. Until we tracked Scarcella to a sauna in a Russian bathhouse, where he started to talk..and talk and talk. “The guilty have gone free,” he whispered. And then agreed to take us into the belly of the beast. Welcome to The Burden.