We are the guinea pig generation. The reality
is as a medical field, as the best physician
in the world, we just don't know. Do you think
patients just don't know that we don't know?
Most people understand what that is on the surface,
but and I honestly just think that as physicians
we probably don't say that enough. It's challenging.
The problem is we have all this access to all
these different tests and the imaging is only
getting better and better. And so I think we're
in this weird kind of bubble right now where
We have this amazing kind of technology for testing.
We don't have a way to truly interpret it yet
because we don't have like the data for it. You
know, I just had this itch to go into the startup
world myself. Didn't have the courage to do my
own startup, but wanted to join one. So I joined
the company General Medicine. If I could go back
10 years, I would have probably told that person
to... Hi, Adam. Thanks so much for joining us
today. Happy to be here, Rashad. Looking forward
to the convo. So let's give our audience a bit
of an intro. Could you tell us what do you do
in your professional life today and how did you
end up here? Yeah, happy to. I'm a physician,
I guess, first and foremost, but didn't kind
of land on that path. I'd say the traditional
way. I started college thinking I would be a
math teacher. We were just briefly chatting about
math background and prowess. I was also just
pretty good at math and it was just natural.
I liked teaching people and helping my classmates.
I picked that as my initial major, but I played
basketball in college too. I was really into
training and performance and making myself as
best as I could be personally as an athlete.
And I ended up pivoting to the exercise sciences
for my undergrad degree. So, you know, which
was, I don't know, it was sort of like a pre
-med light type of major. I took an intro class
and I realized, man, there's a lot of different
aspects you can go into this. And, you know,
selfishly in college, I was like, man, this is
going to be helpful for me to know how to exercise
and how to train and learn about the body and
how it adapts and that sort of thing. I got really
into that, really into strength and conditioning
performance as well. As an athlete, I was good,
obviously good enough to play in college, but
I wasn't great. I had to really work hard to
be that differential. I finished college thinking
I would go into exercise sciences, but I wasn't
sure which avenue because you can go consumer
or more clinical type of roles. I just decided
to try both of them. I worked in some gyms. I
worked for some companies that had their own
kind of fitness kind of program internally, did
that out of college. But I decided to go to grad
school. And in grad school, I dipped my toe in
my first clinical kind of role, which was working
in cardiac rehabilitation. And so cardiac rehab,
I was like, man, this is fun. I got to do stuff
in the hospital and bedside teaching, education.
and then got to work with patients, you know,
in the outpatient facility, crafting their exercise
programs and nutrition and education. So I kind
of always followed that like kind of teaching
kind of arc. I thought I would be a teacher originally
in college, you know, for high school and maybe
coach. I had a mentor there and she was one that
suggested, you know, have you ever considered
medicine? And I was like, no, I haven't, didn't
have any doctors in my family. So it really wasn't
ever really on the radar, but I thought it was.
interesting in a good way to kind of go forward
with, you know, the way my life had been. And
so that took me to medicine. And I think like,
you know, I was in college in the late nineties.
So right when, you know, the internet was really
blooming, you know, and Napster was around for,
you know, free MP3 downloading, obviously highly
illegal, but everyone was doing it, you know,
and I just got really into the technology stuff
that was coming up. So that whole arc was kind
of like woven in throughout and always thought
technology and medicine was something that I
was super interested in. And so I always gravitated
to those types of things. And, you know, I think
in residency, that's probably when I first started
really getting involved when our hospital system
was transitioning to Epic as a EMR going from
paper to Epic. And so I was one of the resident
representatives on that transition. That just
kind of was the catalyst that led me down a path
of like really wanting to optimize the systems
that physicians and other care teams use. It
just made my own life so much easier and better
and more efficient. And I loved being able to
help others do that. So that is kind of what
led down the path of informatics formally. And,
and so, yeah, so I just I did that internally
at Kaiser for many, many years, ultimately becoming
the CMIO for the Colorado region of KP. And,
um, and really enjoyed it, but, you know, I just
had this itch to go into the startup world myself
didn't have the courage to do my own startup,
but wanted to join one. So, um, in August of
2024, I, um, I left KP and I joined the company
general medicine, which was really early and
incubating at that time, but. started with them
part -time and have continued to work with them
through today. That is an amazing journey and
I have a million questions. Let's maybe go in
chronological order. Sure. One thing I really,
and my math journey stopped after first year
of undergrad. The one thing I really enjoyed
about math is you can test everything, you can
prove everything as part of learning math and
doing math. That doesn't exist in the real world.
Often what I found when I was doing my pre -med
courses, eventually the answer is we don't know.
for I found most of the things. They come from
physiology to biology to chemistry. Like often
it's like, we just don't know why this happens.
You know, good example, maybe the Lasix has no
mortality benefit, but obviously it works. No
one's going to not use it for heart failure.
Is that something you struggle with, with having
the very defined worldview in math, at least
at the university first year level? And I'm sure
it gets more vague as we go further along. versus
kind of being in the real world and real working
scenarios where most things are unknown. There's
a lot more probabilities as opposed to determinism
happening. And how do you kind of tie that into
how we naturally want a deterministic model of
the world, but the world exists in a probabilistic
model? Yeah, that's a great question. You know,
I don't think I ever made the connection. Between
me liking math and like what you just said, but
that it actually makes a lot of sense I've always
been someone who when I'm learning something
new I can typically grasp it pretty quickly and
I think for math it was that was particularly
evident and you know, so like we could learn
a new concept and say high school and calculus
and You know, it's like once it clicked and it
clicked pretty quickly. I would be like, okay
I know how to do this. Like I understand the
rules. I understand the formula, etc I think
what I quickly learned and would help me like
Excel in math at an early age was I could then
like translate that to other people pretty easily.
But that was, I think something that was just
like a natural kind of gift that I had. You know,
I think that piece is probably the piece that
I think transferred some like much more to medicine
because as you know, you're always like learning
stuff. You're taking in kind of, like you said,
real, real concrete, possibly even deterministic
things. And then. there's like that gray area
where there's the uncertainty, the, you know,
and so, I mean, I tend to write about this type
of topical bit too, but it's, you know, for me,
like in medicine, I think the way I see it is
I want to optimize the crap out of the deterministic
stuff. Like make that like just so foolproof,
like super easy for patients, super easy for
clinicians. Make that part as like automated
and amazing as possible. Because then I think
then it leaves like more of that kind of gray
area to actually focus on. I don't know. That's
the way I would kind of answer, you know, your
question. I kind of took it my own way a little
bit, but I think that's, um, that's kind of like
been my approach. And that's the part where I
see, you know, us being able to actually be able
to care for more people with less human resource
is to do that. We got to automate the automatic
stuff and the easy, you know, easy in quotes,
but the you know, the deterministic, the algorithmic,
those types of things. We've got to make those
really simple and easy so we can take care of
more people. That's been, that would be my connection,
I think, to kind of the math roots to where I
am today. A lot of VCs in particular, but people
in general have predicted the AI physician happening
in our lifetime and recently within the next
five years. I think the future is easy to predict.
It's very hard to predict when it will happen.
We'll have flying cars, I don't know when. at
some point in the future, we will. When do you
think the AI physician is happening? I know there's
a very early bill in the Senate pushing this
as well. When do you think that's gonna happen?
Yeah, I mean, I think I generally say the similar
thing that you just said, that I'm pretty confident
it's gonna happen. And I think whatever time
I'd say somebody with a more conservative estimate
says, my general gut is that it will be quicker
than that. But I still do think it's gonna take
some time. Is that nebulous enough of an answer?
I mean, I think it'll honestly be iterative and
kind of progressive in a certain way. I mean,
I see more of the kind of more innovative startups
probably pushing the envelope and kind of pushing
what different AI tools can do for care. And
it'll be a much longer adoption curve for the
traditional kind of legacy health systems, you
know, that just have a lot of reasons why they
can't change really quickly. But, you know, I
think like anything, they'll probably be a disruptor
or significant disruptors that I think will catalyze
this and will kind of force it to spread. And
I truly feel it's going to be something that
truly patients gravitate towards and they demand
it, right? I mean, I think that's the way it
happens in all. aspects of our society is ultimately
it's the customers that really will drive it.
And so that's why I try and, you know, kind of
beat the dead horse of like, I really feel strongly
that physicians and other clinicians need to
really be leading and pushing this forward and
really testing and trying things and not being
so guarded. Because I think if we protect the
old ways, I think you're just, you're going to
get usurped at some point. It seems like Chad
GP and maybe OpenEvidence are sort of leading
the forefront here from a consumer DTC perspective
where there seems to be there will be a solution
now where consumers and patients can upload their
records into Chad GPT bleed records. Epic is
building this as well with Cosmos and other tools
where you can ask queries. from your records
what are your general thoughts and that is an
obvious fear that everyone ask do i have hypermaldia
ADHD and not to say that you know those conditions
are very real i treat a lot of patients with
it but the social media push towards if you have
these symptoms you have this. That sentence is
as it can be very dangerous and that's a little
bit of knowledge can be dangerous thing no physician
diagnosis something from four symptoms. Right.
I think you just need more information there,
right? Correct. Yeah. Do you think this is good
or bad? I think if the LLMs are tuned a little
bit differently, not just tuned for validation,
not just tuned to tell me I'm the smartest human
being ever to walk on this planet, which I know
I'm not, then I can see this actually being good.
But the problem is then people won't use it.
We're kind of in a catch -22. This could be really
good, but then it... it won't get usage and that
the quote unquote bad versions of this, the validated
versions of this will probably get more usage.
What are your thoughts here? Yeah. I mean, I
think we're in this weird position right now
where the tools, you know, like the consumer
grade and just take chat GPT or Claude or Gemini.
I mean, all of them are, they're extremely good.
And like you said, like they're pretty darn good
with clinical things. Like I think the challenge
right now, yeah, is like, I think If you just
use the generic model and just kind of upload
your stuff, present your information, and ask
it a simple question, I don't think it's going
to generate something that is consistently accurate,
because they really are kind of aimed to please,
right? That's the way these models really function.
I think OpenAI just recently published a thing
where they said that's the reason why these things
actually hallucinate, because it's actually designed
to do that. It's designed to kind of give a convincing
answer to something that may not actually be
true. But I think, you know, there are ways to
kind of make guardrails around these things too,
even in the open kind of models that are out
there for consumers. I think the challenge is
like, either the consumer has to be savvy enough
to put around their own kind of prompting guardrails
around these types of things and use it in that
way or they have to like constantly be fact checking,
you know, everything with another source, which
is obviously you don't know what to fact check
when you when you have all that. And I still
think though, from like, the standpoint of patients
being able to kind of noodle on their kind of
concerns, their health information, their data,
their different studies and things in labs that
have been done, and to potentially like poke
and look for other potential explanations, I
still think is overly positive. I encourage patients
to do that. I think the part where you just have
to be careful and stop is if it does say something,
you really do need to get that validated by someone
who knows, you know, or knows where to look up
that information accurately. So I think like
where things are right now, where I think these
models are extremely good is On the clinical
side, so someone who has a clinical mind or say
like a lawyer, like someone who has law experience
and knows how to infer which things are wrong
and not. If you have that expertise and you have
the right guardrails and prompting around these
tools, they can be extremely, extremely accurate
and powerful for what you're trying to use them
with. So it's going to be wild. I think we've
hit some crazy leaps and bounds with the LLMs
that are out there. And maybe we're hitting a
little bit of like, I wouldn't call it a plateau,
but it's maybe a little bit of a flattening of
the ascent. But I still think there's going to
continue to be significant gains over the next
few years that handled in the right way are going
to be really powerful for both clinicians and
consumers. From what little I know about athletic
performance and kinesiology, and it is very,
very little, it seems like we don't differentiate
as much between physical and mental health as
we do in medicine. Something I'm thinking about
a little bit more recently. We seem to just look
at them through completely separate lenses where
it's part of the same human body. I don't know
why we have this arbitrary distinction of mental
health versus physical health. We're looking
for an organic cause of mental health, right?
Instead of just saying, this is health. And I
think we would be much better off as a field,
as a society, if we just got rid of the label
of mental health. Because it's almost as if something
is broken with you or in you. Whereas physical
health, you know, no one says if you have diabetes,
something's broken, you're broken, right? Whereas
if you have depression, like people might say
you're broken. Why do you think that is? And
I kind of see this in the longevity space as
well. It's all about physical health. You know,
how do we get rid of this distinction? Can we
get rid of the distinction? Why do you think
it exists? And I have a follow up question I'll
ask after. Yeah. No, I think humans love to compartmentalize
things and traditionally in medicine, I mean,
it's always been very compartmentalized, you
know, over our careers. We've even just seen
how much of an overlap there is, you know, across
disease states. I think that just comes from
historical context of why it is established that
way. But like you were alluding to and what you
were mentioning, physical problems can lead to,
quote, mental problems in yourself. And mental
problems can obviously lead to physical problems.
So they're clearly tied together. I mean, I think
what I a lot of times break down with patients,
because I think, too, patients, if they come
in with a symptom, say they come in with abdominal
pain, And everything's been kind of ruled out
from from a, you know, an actual digestive functional
or a physical problem. And, you know, you ultimately
arrive at something, you know, like, you know,
IBS or something that's just, you know, this,
and you start explaining it to them. And the
way I always break it down is that, you know,
our brain and our gut are like actually directly
connected by the same nervous system. And Because
if you just jump right to saying, hey, I think
this is, is IBS and, you know, we should try
X, Y, and Z that, you know, and then they go,
wait a minute, those things you just mentioned,
those are like, those are medicines that are
used to treat depression and anxiety. Like, how
is that going to help my gut? I mean, I think
that's just like a perfect example in medicine
of where there truly is that connection. But,
you know, I mean, personal story for me, I mean,
when I, I've had periods of my life where I've
had some pretty significant orthopedic injuries,
you know, from, from athletics. happened first
in college. I broke my foot and had to have a
screw put in there. That put me out a year. I
was definitely depressed during that year. I
mean, I clearly had some depression, but it was
clearly related to, you know, a physical ailment.
It happened to me again, you know, later in my
adult year, you know, probably my 30s. I tore
my patellar tendon and, you know, that really
put me down and like even got me to the point
where I was like, man, I can't play basketball
anymore. And So there's been like these waves
of things that have come and I think those two
things really are connected and I'll flip it
a little bit to like, I hate it in healthcare
where things are compartmentalized too, right?
I mean, we need specialties and specialists for
different expertise, but like, I absolutely hate
it when a specialist would be like, oh no, we
can't talk about that because that's not my specialty.
I think that's BS. Like every specialty has an
overlap with something else, right? It's the
human body. And then the terms we use in healthcare
are also compartmentalized. Like, why do we call
it telehealth or digital health or in -person
health? Like, it's really all the same. I mean,
the goal of it all is exactly the same. So, I
don't know. I think it's just humans. We like
to compartmentalize things and put things into
a bucket. You know, I think the whole system
has been set up that way, you know, from history
until now. But I think there's a little bit of
a shift. So much of the foundation is still.
rock solid in that area. We know what we need
for longevity and for athletic performance to
an extent. We know we need to sleep seven to
nine hours. We need to reduce our stress levels.
We need to let go of thoughts that are harmful.
We need to eat better foods. Ideally, a more
plant -based diet. We need to lift weights. We
need to do cardio. None of these things require
any technology. Yet, it's technology and AI that's
unlocking the longevity space. It's tests we
don't need, it's more biomarkers we don't need
to an extent. There is some role for imaging,
for market detection of preventive health in
general. I'm not saying preventive health shouldn't
exist. But do I really need a biomarker for sleep
or for lifting weights? Do you think we're at
a point where... We are testing too much and
not optimizing for what's needed. Or do you think
given the way our human brains are designed for
convenience and reward and scarcity and, you
know, the principles of marketing, we need to
do it this way? Yeah. I mean, I don't think it's
like an either or. Um, it's one of those things
that, you know, kind of like you just said, I
can be on, I can be on both sides of the fence,
you know, like, you know, I mean, I think, and,
and I think there's a, there's a tug and a pull
between traditional quality based health care
and what consumers actually want and need to.
So I think there has to be a balance between
these things, you know, and that's, um, you know,
so like I've had plenty of conversations with,
you know, my neighbors who know I'm a physician
and they'll just be like, you know, why wouldn't
I go into the doctor? Like, why won't they just
let me, why won't they just order everything?
you know, to make sure everything's not right,
wrong, right? Or, you know, we have several companies
that are doing kind of whole body imaging, you
know, to try and look and see if there's potentially
anything. And, you know, on one hand, I totally
understand that, like, right? I mean, you want
to know, like, it's like this element of unknown.
But I think, like, you know, if you go into the
actual, like, statistical probability of these
tests being positive, and you get into all the
details of that, like, you quickly realize that
it's not really good to just blankly do all of
those. I think what we have to do is we have
to find a way that these tests can actually be
much more sensitive and much more specific, which
is obviously the holy grail of any test, right?
You have those both at 100%. You're like pretty
much money. You can use it as a screening test
and confirmatory test. And I think that's like
where we just have to really push with these,
you know, so -called biomarker tests, which I
hate that term because really all of it, it's
the same things we always have. They've just
tagged on a catchy name. But, and then I think
the other thing, obviously everyone wants to
live a fruitful life and everyone wants to live
a long life, right? I mean, unless something
horrible happens to you that you're miserable.
I think this whole rush for kind of longevity,
I wish it wasn't called longevity because that
infers that people just want to live longer.
And I really think like, What people really want
is they want to live the way they are right now
as a younger person for a longer time. You know,
and there's all sorts of obviously terms and
things that are used for that. But I think it's
like, if all of this is truly just allowing people
to live a longer, fruitful life and be able to
do the things that they want to do for the longest
period of time, then I think that's good. But
I think this whole like, I don't know, the whole
industry around hacking different things and
trying to find certain things that are going
to degrade aging and uh, be able to prolong different
cell life. I don't know. I just think that's
we're like splitting hairs at that point. Cause
like where you led with all those core tenants
are really the things that if you do those, you're
pretty much going to live a good healthy life.
And I always tell patients, especially my older
patients, you know, or that are patients that
are approaching an older age. Like it's even
just more important that you do those basics
when you get older, right? Like you've got to
preserve that strength. I mean, cause If you
fall down or you slip and you're on the ground
and you can't get yourself up, I mean, that's
a problem, right? Like a little kid, I mean,
they fall all the time, hit their face, they
bounce right back up. But just getting on and
off the toilet or slipping in the shower and
not being able to get yourself back up, I mean,
those are the things that can really do people
in. I don't know, that was like a serendipitous
answer to your original question, but I think
all this stuff that's happening right now is
very well intended, but I think a lot of people
are jumping on the bandwagon of this term, longevity,
to like promote stuff that we've kind of like
already known or can already do. I haven't really
seen a ton of net -net new things, but I think
some of those are probably on the fringe of really
coming together. Yeah, I think going a little
bit deeper, you know, I had a patient who wanted
a screening x -ray for no reason and ended up
with a lung resection. But you know, these cases
are rare. I can almost guarantee if we give you
every single test we know, it will result in
some invasive treatment for no reason. And the
gap between what we know in medicine and medical
knowledge and the appetite for knowing and optimizing
our health is very wide. We know so little. about
what to do with the test we order and even though
the normal ranges are based on specific populations
that maybe don't apply to other populations and
they're based on gender and age and race and
medical conditions. So I think there we are the
guinea pig generation and I think collecting
more data is good. We don't know what to do with
it and I think patients should know that before
signing up for these things. This is an amazing
business opportunity. You feed people more uncertainty
every time you order more tests because we don't
know what to do with them. The reality is as
a medical field, as the best physician in the
world, you know, whatever the top doctors from
wherever you think are the top doctors from,
they don't, we just don't know. Like, I don't
know if your sodium is 134, what does that mean?
I know if it's under 130 that, you know, maybe
we should optimize it a little bit because it
can lead to bone demilitarization. And if you
have a hyper, if your sodium is too high, Sure,
I should look for maybe something called diabetes
insipidus. But we don't know, there's no optimal
sodium, right? Like a 137 versus 136, there's
no difference. And I don't know if that's an
answer people just aren't willing to accept.
Or is it like, no, you know something, you're
not telling me. Whereas I'm like, why would I
hide it? Why do you think that? Do you think
patients just don't know that we don't know?
How do you kind of deal with the question? Well,
why wouldn't you order every single test? Like,
I want to know my complement pathway, right?
I want to know everything, right? Like, all the
genetic tests, you know, and all the tumor markers
every single visit. Because if I get cancer now,
I want to know now. I want to follow CA -99 hourly.
And so the audience is not medical, the tests
I'm measuring, mentioning CA -99 is a tumor marker
for pancreatic cancer that we use in ovarian
cancer. we use to monitor cancer, but not to
detect it, because that's not what the test is
designed for. And we just don't know what to
do if it's a little bit high, because a pancreatic
is not an easy procedure. But anyways, like,
what is your kind of answer there? Yeah, I mean,
my approach to it is generally like, just this
true like shared decision making approach where
I'll try and break it down to the patient of
like, you know, this test or these tests are
for X, Y and Z, but I usually will get a pulse
of like, how much this person wants to dive in.
Cause I can go into a whole deep dive of what
sensitivity and specificity are. And I think
people, most people understand what that is on
the surface, but you know, when you specifically
dive it in, dive into testing, I think that's
when people really can kind of realize it. And
then, you know, I'll flip and I'll start talking
about positive predictive value and negative
predictive value and like these types of things.
And, and that all tests like vary and some of
them, you know, like say, like those tumor markers
that you're mentioning. I mean, those things
can be really kind of horrible at some of those,
but then also can be really good for some use
cases. And so I think a lot of people think labs
are very like black and white. And, you know,
I think you asked the question specifically,
why do patients have like maybe that skepticism
around physicians and kind of the interpretation
of these things? When in reality, a lot of these
things, we don't know what they mean, right?
I mean, it's And I honestly just think that as
physicians, we probably don't say that enough.
I think patients expect us to just know everything,
but like, you know, I think family docs, you
know, biously probably do this a little bit better,
but I think we're well, we're generally better
at like saying, yeah, I really don't know what's
going on with you. I agree. Your symptoms, you
know, are disturbing and we've checked X, Y,
and Z and they've all been okay. But I think
where this gets into trouble is when there are
some practitioners out there that will start
to say, oh, there's this optimized level of this
and that. And, you know, I've encountered this
as a doctor, patients will bring me these reports
and, you know, it's like a standard Quest lab,
but like it has this custom kind of interpretation
of it. And, you know, patients are like, oh,
they're telling me I'm not optimizing this and
that. And I'm like, well, I don't know what to
do about that. You know, like drink more water.
Like if you're, you know, creatinine isn't dead
in the center of, you know, the creatinine range
or less water. I don't know. It's like, yeah,
it's challenging. The problem is we have all
this access to all these different tests and
the imaging is only getting better and better.
And so I think we're in this weird kind of bubble
right now where we have this amazing kind of
technology for testing, but like what you kept
saying, we don't have a way to truly interpret
it yet because we don't have like the data for
it. You know, like I'll take whole body MRI.
as an example, I'm like pretty bullish that that's
going to be something in the future, like that's
going to be pretty transforming to healthcare.
I think right now most physicians are super skeptical
of it because of the way we were trained and
the way things are, right? I mean, cause you
don't want to just find all these incidental
things that you're chasing down and people are
having biopsies of and all this follow up, you
know, like that's especially if it turns out
to be nothing. Now you just put someone through
a bunch of risk, but I think if the imaging in
these tests can continue to get better and better,
and the technology that interprets them, including
the physicians, gets better and better, we will
reach this point where it's a really, like I
said originally, where it's extremely sensitive,
but it's also very specific, and being able to
characterize specific findings and not just be
that kind of... typical radiology read that like
hedges on something like looks sort of concerning
but not definitive. I think we need to get to
a place where we can definitively characterize
things better because I think that will ultimately
lead to better outcomes and better prevention.
Pulling on the whole body MRI thread and I do
recommend it to some select patients who I think
are a good candidate with family history of cancer
or patients I know will be comfortable handling
incidentalomas. From talking to a radiologist
and an oncologist friend, what they kind of,
their frame of reference is a whole body MRI
will never diagnose cancer because we cannot
see the pathology slides, right? Like we cannot
see in a system, it's magnetic waves, right?
Like we cannot see inside the detail because
the technology is limited. The MRI technology
itself, the way it works is limited. So you cannot
see through a wall, no matter what the resolution,
no matter how many pictures you take. You're
never going to be able to see through a wall
because you're using light and light does not
travel through walls. That's kind of their analogy
is MRI will never diagnose cancer. The only way
to train a model is to take a biopsy of every
single incidentaloma to then train a model to
have enough data to say this is cancer, this
isn't cancer. What are your thoughts there? Do
you think we're... Doing cancer screening a disservice
by leaning so heavily into MRI and because they
have this mythical Connotation somehow that's
developed that it shows all when you know, it's
still a picture You don't see the actual tissue
or the actual cells and cancer is for those that's
in cancer is very fast dividing cells and we
see them under a microscope on pathology slides
we can see cells in an MRI no matter how much
you want to, I don't know, whatever you want
to do with MRI, just like we can't see through
the wall, no matter what you want to do with
the light, or you can't see inside a ball with
light. Yeah. So like, what are your thoughts
there? Like, should we be building a technology
that allows us to see at a cellular level based
on a non -invasive test? I think that's what
we should be building, not wasting our time with
MRIs. Like they have such a big commercial Tailwind
that it's it's all it's easy enough to say well
the outer hole better MRIs a lot of people get
they will make a lot of money kind of thing Yeah,
no, it's good question. I think we're gonna have
to wait and see how the technology evolves I
mean, I think I think in the MRI realm I think
just what's improved significantly in the last
few years is there the Obviously the quality
of the machines continues to improve but I think
the other piece that's really changed and improved
is the quality and the configuration around the
protocols of like how the image is rendered,
you know, like on the actual screen. And so I
mean, are we going to reach a point where like
you can no longer improve what the image looks
like and you got to look for some sort of new
technology? Like you just mentioned, could there
be some other sort of thing that could actually
get to the level of like a pathology kind of
evaluation through, yeah, some sort of light
or image or something, you know, I mean, I think
there's definitely a possibility that that could
come about. Not aware of anything in the R &D
area around that now, but I'm sure people are
trying to look for those. I just think, you know,
with what we have today, I think what will be
interesting to show over time is if doing any
of this stuff actually changes some sort of outcome.
You know, I think that's going to be the most
telling thing. Will there actually be positive
outcome data from these types of things? And
I think that's still to be told. And I think,
you know, the emerging companies that are doing
this, or that at least started doing this, I
think that's why they're collecting this data.
I think they're hoping to be able to show that
sort of thing. Because yeah, as of right now,
none of that stuff is, none of this can be covered
by insurance yet until there's some sort of real
substantial proof, you know, that it's going
to change the outcome. I think we'll probably
get there at some point. I just don't know what...
timeframe that's going to be. And so for right
now, I think these types of things are going
to live in the kind of the cash -based business,
you know, or companies will offer it as a perk,
you know, as being a part of the company to get
these not current evidence -based, you know,
testing and exams done. I think time will show
eventually it'll show either yes or no. And that
could be kind of either the bloom or the doom
for, you know, these types of things. I love
the framing of focusing on the outcome. It's
easy to get lost in the technology and the details,
but what matters is outcomes. Yeah, so time will
tell. What do you think went wrong or went right
with the Brian Johnson experiment where he kind
of launched this, grew it, and then it seems
like he said maybe I've had enough or it's not
working? Do you think that's kind of a case study
and, you know, just sleep better, exercise more,
lift weights so you're struggling a bit, doesn't
matter how many reps you're doing or how much
weight you're lifting as long as you're pushing
yourself? that's what you want. And then tracking
these things isn't the path to optimization,
pushing yourself, sleeping better, being less,
because you know when you're less stressed. I
don't need anything to tell me if I'm not stressed.
What are your thoughts on the Brian Johnson phenomena
and then just the tracking all these things in
general? Yeah, I mean, I think the tracking piece
is like, you know, it's one of those things that
I think is helpful for some and it can be very
kind of anxiety provoking to others. And there's
like a spectrum in between, you know, I think
like so recently I've probably for the last six,
six or seven weeks I've been using, you know,
one of the, the Stelo CGMs, you know, just to
track what my sugar does. I don't have diabetes.
I don't have pre -diabetes, but, you know, I
think what's been pretty eye -opening to me is
just it's all the stuff that you kind of know,
right? Like the more sugar you eat, like the
higher your, the steeper your spikes will be.
And then on the flip side, you know that, I mean,
I guess my background in exercise, I know what
happens from a, like a biochemistry perspective
for exercise with blood glucose and, and that
sort of thing. But to actually see like what
happens, you know, when you just When you do
any sort of exercise, whether it's in the morning,
the afternoon, or in the evening, and when it's
around food, you can visually see the changes
that that does. I think for some people, having
that data is really helpful. I've had plenty
of people where I think they're just trying to
get so much data and you become obsessive about
it. I think if you can use it in the way that
it will help you to make behavioral changes,
I'm all for it. But I think that has to be framed
up. And I think when patients ask me, oh, hey,
should I get this sleep tracker and do this and
that? I usually have a conversation with them
a little like, what are you hoping to get out
of it? And how do you plan to use the information
to help yourself? And as long as they have a
good thought process around what they're going
to do, I'm usually supportive of it. If I can
tell they're like a super anxious type and that
they're just, this is probably just going to
make them super, super nervous all the time.
You know, I'll probably be trying, I'll try and
steer them away from it if possible. But so yeah,
I think it's like kind of like, I think it has
to be adaptable to the type of person that they
are, you know, if or when this is going to be
helpful or not. Earlier, you said that you are
excited about technology in healthcare and optimizing
systems. If you could magically optimize our
In one system and healthcare, what would it be?
So, I mean, the thing that's been on my mind
for a very long time is, you know, there's a
lot of, I think if you ask that question to a
lot of people, they'll say like Pyrros or the
in basket or whatever. I mean, because I think
a clinician that's like what we're so, and I
agree technology can fix all of those things
pretty well, but I would zoom out even further.
And what I really want is like, I want patients
to have the ability to really kind of. um, accurately
kind of noodle on their concerns and really allow
them to like frame it up. So the time spent face
to face or whatever it is with, with the actual
kind of physician or clinician is like extremely
efficient. And so I guess the way I would like
break it down is I think we need still need better
ways kind of pre -encounter how for patients
to really formulate. what their concern is and
what's going on. Like we have pretty good stuff
right now to be able to help within the encounter
and like synthesizing and capturing. We need
even better tools downstream, you know, like
the post and across like between visits. I think
right now, like patients have real, real concerns
about themselves or their health. And what we've
done is we've made it so they only get to spend
10 minutes with the actual like expert for this
like one for this problem. And I just think that
is like, it's not right. I mean, it's like, they
don't remember anything that's said during those
10 minutes. It's like, I don't know that that
was a kind of a long winded way to your question,
but I really do think we just need to, we need
to optimize that the whole process of From concern
to the patient feeling like they're getting some
sort of resolution or next steps. I think that
is still fundamentally like the same as it was
when I was a child. It hasn't changed. So I want
technology to be able to fix that stuff. As clinicians,
we often kind of forget the patient perspective
of things. We're so entangled in our inbox and
prior, as you said, that it's difficult to kind
of see their experience. And we just want to
kind of get to the bottom of the medical query
and solve it. Yeah. Yeah. So I can definitely
see, I'm not sure the business model or the business
case there, but I think there's this fairly a
need there. Last question, Adam, if you could
go back 10 years in time and talk to yourself,
what would you tell him? Well, I think like just
what I went through last year, you know, I finally
made this kind of proverbial leap to something
that I wanted to do for a long time. If I could
go back 10 years, I would have probably told
that person to follow that, you know, desire
and instinct. I had a lot of people telling me
over the years, like, you know, you should start
working in the startup space or you should, I
can see you doing X, Y, and Z. And I just kept
going, yeah, I do too. But I never took the leap.
So I would honestly just go back and tell myself
to take the leap earlier. Well, congratulations
on taking the leap. And I'm happy to meet a fellow
physician entrepreneur and a physician in the
start. No, you bet. Thank you. I appreciate it.
Great conversation.