August 14, 2024 • 36 mins
On this episode, we explore the cost effectiveness of computer assisted versus conventional total knee arthroplasty. Joined by special guest Dr. Hassan Ghomrawi, surgical outcomes researcher/health economist and associate professor at the Orthopedic Surgery Department of the University of Alabama at Birmingham, the discussion delves into the economic incentives and outcomes associated with these advanced surgical techniques.
Dr. Ghomrawi shares his unique journey from pharmaceutical economics to orthopedic research, offering insights into how different healthcare models impact cost and patient care. The conversation also touches on the broader implications of technology in orthopedics, including wearable devices, robotics, and artificial intelligence.
Listeners will gain a comprehensive understanding of the study's methodology, including the use of markov models to simulate patient outcomes and costs over a lifetime. The discussion includes the potential for increased utilization of computer assisted surgery, the role of insurance payers, and the future of cost effective healthcare solutions.
Follow us on (X) and Instagram @theskcpodcast, visit our SKC Podcast YouTube and Facebook pages, or email us at theskcpodcast@gmail.com
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Music.
(00:12):
This is Dr. Benner here for another episode and some more new content.
Another JBJS article that we're going to be talking about tonight.
And we have another author from one of those articles on tonight.
So we'll introduce our guests in just a minute. If you want to find us on social
media, you can find us on Twitter and Instagram at the SKC Podcast.
We have a YouTube and Facebook page for the Shelbourne East Center Podcast.
(00:32):
If you'd like to email us, you can email us at theskcpodcast at gmail.com.
If you like what you've heard for this episode or any of the other ones,
leave us a five star review and a comment for those that come behind you.
And also check out our previous content.
We have over 40 episodes about new topics, and we'd love it if you'd go back
and listen to any of those.
Specifically last week was a great episode. We had a true leader in the field.
(00:53):
We had Dr. Liza Aaron from the University of Minnesota, and we had a great conversation
regarding and centered around the treatment of Patel for moral instability.
And she did a tremendous job. It was a great conversation. She has such great
historical perspectives.
She's been doing this for a long time, working with the athletes at the University
of Minnesota and elsewhere.
And she did a tremendous job discussing the exam, how to take care of these
(01:17):
patients, as well as some surgical techniques for the patellofemoral instability patients.
So go ahead and check out last week's episode to check out the patellofemoral
episode from Dr. Liza Aaron.
Tonight's guest is Hassan Gomrari. He is an associate professor at the Orthopedic
Surgery Department at the University of Alabama at Birmingham.
So he just joined UAB just a couple
(01:38):
of months ago. He is the Vice Chair of Research and Innovation at UAB.
He's also the Associate Director at CAMBAC, which stands for Comprehensive Arthritis,
Musculoskeletal Bone, and Autoimmunity Center.
And we're going to be talking to him tonight about a study that was recently
published in the Journal of Bone and Joint Surgery titled, The Cost-Effectiveness
of Computer-Assisted compared with conventional total knee arthroplasty,
(02:02):
a payer's perspective. So, Dr.
Gomorawi, thank you very much for joining us, and we're happy that you've joined
us on the podcast tonight.
Yep, thank you for having me. Very good. Well, tell us a little bit about your background.
How did you get into this line of work, and how did you, you know,
you're just telling us off-air a little bit about joining this new opportunity
at UAB, and we're just curious about what your background was and how you got
(02:25):
to this position. position?
Yeah, I have a slightly different sort of background than what people would
usually be thinking about how I came to become an orthopedic health services researcher.
When I was doing my master's in public health at the American University of
(02:45):
Beirut, I really wanted to become a,
a pharmaceutical economist and i was doing this study where in lebanon generic drugs are not.
Used they only use brand name drugs and so we did a study comparing generics to,
(03:05):
brand names and the cost savings and i was mind blown by how much savings our
economy could save by using these drugs and so i wanted to be a pharmaceutical economist this.
Applied for the PhD program at the University of Minnesota, got into the program.
Actually did almost a thesis around pharmaceutical economics, didn't work out.
(03:31):
I got this research assistantship with an orthopedic surgeon at the University of Minnesota.
He was doing a multi-center revision neuroplacement study, and I became the
research coordinator for that study, learned about patient-reported outcomes,
got really excited about that.
(03:53):
And that's sort of how I got into orthopedics.
I realized very quickly that there are very few people who know health services
research and also know orthopedic outcomes.
And so I realized quickly that
I could make a big dent in orthopedic outcomes if I get into that field.
(04:14):
And I made the shift from pharmaceutical economics to orthopedic outcomes research.
The nice thing about that, although it was really painful at the time,
was that I was able to act as an outcomes researcher, but also as an economist at the same time.
So I could look at the same problem with multiple lenses.
(04:39):
And then after that, I got the first faculty position at at the renowned HSS
and Weill Cornell Medical College and then was recruited to Northwestern for another few years.
And then a few months ago, UAB made me an offer that I could not say no to. And here I am.
(05:00):
Very good. Well, I appreciate your coming on tonight and an interesting background.
You know, we're getting a lot of economic pressure in orthopedics,
as in all of medicine, to try to get costs down, to try to be cost effective.
And at the same time, there's an explosion of technology in orthopedics as well.
Wearable technology, robotics, computer-assisted navigation,
a lot of talk about AI at meetings and what the future is going to be with artificial
(05:24):
intelligence, et cetera.
And it's an interesting dichotomy to have the micro-level stuff from at home
where we're all getting shaken down for cost savings and then going to meetings
and just hearing about just a broad expansion of technological resources in our field.
So I think it's an interesting space that you inhabit to talk about the economics
(05:49):
around this and be able to understand the outcomes because not everybody can do that.
So, you know, how many people are really looking at these things in quite the same way as you?
How many of you are there out there that are looking at the economics and the
outcomes and trying to put all that together in order to make some real dents
(06:10):
in a couple different directions that orthopedic surgeons and hospital systems are trying to go?
Yeah, I don't know the universe of people who do this, but I know that there are few.
Because every time I go to JBJS or some other orthopedic journal with an economic
analysis, it's more likely to be accepted than not.
(06:32):
And so I think that the field is hungry for economic evaluations that do evaluate
these technologies and estimate the added value to the economy of using these new technologies.
It's interesting that you've mentioned sort of technology because outside of orthopedics,
I also use wearable devices on pediatric surgical patients to try to predict
(07:00):
complications using the Fitbit data.
I do agree. I think you have a fascinating background. I'm curious,
as you went from pharmaceutical economics to more the orthopedic side,
did you see any parallels with that when you were doing the study on the generic drugs?
And as you made the way to starting to look at this from an orthopedic lens,
did you notice there were big similarities or big differences between the two?
(07:23):
It's not so much the similarities in the content, but more the fact that,
for For example, when people look, when surgeons look at joint replacement,
they only, or most of them, I would say, only look at the clinical side of things.
And so, but in the bigger context of things,
(07:45):
joint replacements, all of a sudden, like almost overnight, became this very
highly utilized procedure that Medicare now thinks of it as a major sort of cost center,
right, almost, and they want to do something about it.
And so when you're looking at genetic drugs saving the healthcare system money,
(08:09):
now we're looking at joint replacement and we're trying to figure out ways to
make that procedure save money.
One thing that in my research I've looked at, and I think Dr.
Benner would not totally agree with me, is the whole concept of appropriateness
of joint replacement, which is sort of let's find an objective metric to say,
(08:34):
these people shouldn't be having surgery.
In the policy arena, they're saying, you guys do whatever you want.
You can do the surgery. We're just going to try to lower the cost of the procedure itself.
And my approach was, no, let's try to reduce the number of procedures being
(08:55):
done if a procedure is not appropriate.
I agree with you 100%. I couldn't agree more. You know, because we are a knee-only
clinic, we have knee physical therapists that work in our office.
And for those listening, you can check out some of our previous content to listen
to our non-surgical treatment of knee arthritis talks that we had,
which we covered in a lot of detail.
(09:15):
And the reason is because we're trying a lot at our office to keep people out
of the operating room, which I know is not something that you hear a lot of surgeons say.
A lot of surgeons are saying, do I need an operation? Do you need an operation? Yes or no?
And if the answer is no, best of luck. Go find something that you can do.
You know, here's a couple of things. I think here's a medicine you can try.
Here's an injection I can give. Whenever you're ready to to have surgery,
(09:38):
just come back and let me know.
And our office works the complete opposite of that. We're always trying to think
of what can we do to try to make you better non-surgically?
How can we keep you out of the operating room?
Because it's interesting when you go to meetings, they talk about how our system
is going to be overwhelmed with the number of knee replacements that we have
to do and hip replacements that we have to do.
(10:00):
And yet, everybody's talking about about what do we do to be able to handle
the amount of surgeries that we have to do.
Very few people, if any, are talking about how do we avoid surgery because surgeons
don't want to avoid surgery.
Obviously, our compensation or how busy we are is all tied to the amount of procedures that we do.
That's a whole other direction we could go that you could probably talk about
(10:21):
as well a lot about is how that plays out with pressures from compensation being
directly tied to procedures and how that.
Potentially affects our decision making a lot but but the point is that you
know i agree with you i think that one of the ways that we handle the economics
around this particular problem and specifically you know do we have enough bandwidth
(10:45):
to handle all the arthritis and all the surgeries that we have to do is how
the hell do we find out a way to not do surgery on everybody yep.
Absolutely yeah totally different way of looking at it and probably a discussion
for another day but but interesting perspective that you have there uh you know
let's talk a little bit about the study that we're here to talk about tonight,
where you compared the cost-effectiveness of conventional and computer-assisted
(11:07):
total knee arthroplasty.
Tell us about how you became involved in that specific topic and this specific
study. What was the genesis of this paper?
Yeah, this paper is, I think, the third paper we published on the topic.
The first paper was just, actually, the fourth paper.
The first paper was just a review of the literature, and And it was a systematic review.
(11:33):
We looked at all the published literature, and we found that more or less computer-assisted
was associated with better outcomes.
And then I decided to start analyzing large databases.
I analyzed data from New York and California and Florida, and we looked at data over a 10-year period.
(11:57):
We saw that there was an increase in computer assisted, but the increase is very shy, right?
Or over that period, the utilization increased from 5% of all near placements to about 10%.
So although you'd say it's 100% sort of increase.
(12:17):
Out of the sort of bigger pie, it's still a very small percentage.
We also published another study, a very recent one, where we looked at patients from New York State.
We took everybody, and then we compared computer-assisted versus conventional.
And we found that the outcomes of computer-assisted were much better than those for conventional.
(12:39):
And so in my mind, I was thinking to myself, there is this procedure that produces
better outcomes, but then its utilization is very low.
And what are the drivers of that?
And so one way that I wanted to approach this was to say, are there sort of financial incentives?
(13:02):
Are the financial incentives playing into this? And that's how we did this cost-effectiveness study.
Yeah, I think my general impression is, as we talked about off-air again,
I'm much more into robotic-assisted surgery as opposed to computer navigation,
and I don't think robotics isn't necessarily akin to this particular paper.
(13:23):
Just correct me if I'm wrong.
That's right. This is just not robots.
Yeah, it doesn't include any robotics. Yeah, but I assume a lot of common things
seem to be there in the literature that I think people agree that we can get
better with alignment using technological advances to help do our surgery,
that our chances of having outlier alignment are less if we use some sort of
(13:47):
technological advancement to do the surgery.
I think that is settled science that it does improve alignment outcomes.
I think it is equally that I shouldn't say equally settled science I used to
think that but I think more as it as more data comes out it's a it's at best
uncertain whether or not this really gives us. A couple of.
(14:08):
An outcome measure an outcome measure
improvement for our patients i think that it probably does
the but you know last meeting we went to stop i sat
in a couple sessions about robotics versus standard instrumentation and saw
side by side you know talk after talk studies saying that it made no difference
there was no advantage to robotics and technology and then right behind it one
(14:29):
that said there was so you know and especially as we've started to add in soft
tissue balancing as well as alignment,
for me, that's been a differentiator.
For me, that kind of pushed me over to eventually now doing it.
And now I've done it for about a year and a half, and I've probably done 300
or 400 robotic cases, then I probably won't go back.
So I think it's definitely a controversial thing, and you seem pretty certain
(14:53):
that the data that you've looked at shows some specific advantages,
while others, of course, say that that's not necessarily the case.
So tell us a little bit about, you know, your previous studies, I guess.
I'll be honest, I haven't read your previous studies, just this most recent ones, on what you found.
So, the previous study that compared outcomes found that the in-hospital complications
(15:15):
were lower, much lower for computer-assisted procedures.
And so, when we did the study, the economic study, we made a few assumptions.
One assumption was that these two procedures, if you do it computer-assisted
or not, the quality of life or the PROs are the same, right?
(15:38):
That it's not producing anything better in terms of functional outcomes.
We also did the study from a payer's perspective.
And I think that's the innovation mostly of the study.
The one who's paying for this is the one who's going to drive this.
And there's a lot of prior literature from other procedures that show that if
(16:02):
insurance covers something.
More people will use it. No doubt about that.
And there's ample evidence from the cardiac surgery literature and other procedures
where if insurance covers it, more people will start doing it.
And so I think that's one innovation in this study that hasn't been talked about before.
(16:25):
The other thing is that we recognize that there are two types of patients.
There are the elderly patients who are Medicare patients, and these become Medicare
patients, and they're insured for life.
And so Medicare incentives are to improve your outcomes for the long run, right?
Versus commercial insurance or something like Blue Cross Blue Shield or similar
(16:51):
types of insurers, they cover people for a period of three to ten years.
And so the time horizon there is different. And so the incentives are different.
These insurers focus mostly on short-term benefits, right?
They don't care if you get cancer in 15 years, right?
But they do care if you're insured by them and you're going to get diabetes
(17:16):
in the next two years or a heart attack in the next two years.
So the way we modeled them, we created two different models.
And so we modeled with a short-term perspective and a model with a lifetime perspective.
The other thing is for Medicare too, we said that there are certain patients
(17:37):
who are covered under a bundled payment arrangement, and there are some who
are covered under a fee-for-service arrangement.
And so we did the same modeling under different scenarios, scenarios and in
all scenarios it showed that the computer.
Was more cost-effective than the conventional. And so, regardless of how you
(18:02):
turn it around, it still shows that there is a benefit to computer-assisted surgery.
Now, Hasan, when you're talking about the genesis of this study,
and a lot of it really stemmed from what sounds like your previous work,
and getting into the methodology of this study, now that you've described those two care models,
can you take just a couple minutes and describe more of the methodology,
(18:23):
especially as it pertains to this Markov model.
I know this is a very interesting way to look at the cost effectiveness and
the different scenarios.
So I know that was a big part of the methodology here. I'm looking specifically
at figure one for those that can go back and look at this JBJS article.
So how did you go about that from a statistical standpoint within the methods?
(18:45):
So Markov modeling is a purely hypothetical theoretical exercise,
right? What we do in these models is that we try to mimic the clinical course
of a patient over their lifetime.
So let me give you an example. A patient has knee replacements.
(19:05):
They have a chance of a complication or no complication.
After the complication, they could get better or they could have further complications.
Or the complication could lead to a revision. revision, right?
They could go for a few years and then have a revision.
And so these Markov models are interesting in the sense that they try to mimic the clinical course.
(19:30):
Very closely. And then we use the literature to try to then,
for each sort of what we call a node, which is a probability or,
yeah, a probability node,
which is like, say, what are your chances of having a complication?
In the literature, there's somebody who's done a study using Medicare claims,
(19:52):
for example, and they found that probability of PE is 0.2%. So we use that estimate
and we put it into the model.
So we're trying to create a clinical course for each event in that clinical course.
We're looking at the literature and finding the estimate that we think is the
(20:12):
best, is the most reasonable estimate.
And then after that, we estimate that model.
And it's sort of complicated, but what it does is that it goes through these
Markov models, goes through a repeated cycle of events until the patient dies.
(20:33):
So it could go for 40, 50, 60 years until the hypothetical patient dies.
And then it rolls back and says, over these 60 years, how many quality of life
measures does this patient get and how much cost did this patient incur.
(20:54):
And then we compare the treatment options based on the course of the patient's lifetime.
That seems a little technical, sorry. No, that was very helpful.
That's what Markov models are all about.
Yeah, and I find those models very interesting. At least in my next question,
one of the big outcome parameters you were looking at were the quality-adjusted life years.
(21:18):
And I know you mentioned that when you run this Markov model and you run through
these thousands of simulations and you can come up and determine the effectiveness.
And that was a big part of the tables that you had.
So when you're comparing the effectiveness and you're looking at those quality
life years, and you're comparing here with 0.82, 0.749,
can you explain how that was determined as it relates to the difference between
(21:42):
computer navigation or computer-assisted and conventional TKs? Yeah.
So just to simplify the quality adjusted life here, it's a year,
but if your quality of life during that year is lower than what we consider as optimal,
then you're getting less than a one unit for that year.
(22:02):
And so if you're living with a lot of disability, your quality adjusted life
here is like, I don't know, 0.6, 0.5.
Some people with like cancer have like 0.4. And if you die, your quality goes
to zero during that year.
And so this is sort of a measure that has been developed primarily because they
(22:25):
wanted one measure that can compare treatment across diseases.
So this is sort of a much bigger conversation about prioritizing treatment.
So things like what happened in, for example,
(22:47):
England at one point in time where they decided that they want to look at all
the treatment options and only pay for those that have provided provide the
highest quality of life, the highest qualities, right?
And so we are comparing cancer treatment with total joint replacement,
with vaccines, with other things.
(23:08):
In here, what we've decided to do for these, as I said, we've assumed that these two procedures,
provide the same quality of life, that there's no functional benefit to computer-assisted,
Although, I think there is ample literature out there that shows that computer-assisted
(23:28):
results in better alignment.
So over the long run, you're going to have less loosening, less rates of revision.
But the evidence that's right now is very controversial.
And the only...
Data that we found that has long-term follow-up on these patients is an Australian
joint replacement registry.
(23:50):
And that's where we got our estimates for the difference between revision rates
for computer-assisted and conventional.
And even for that, I mean, the revision rates are not a lot,
just to be very frank about it.
We need more registries from the U.S. to show us this data. I think there is
(24:11):
reason to do this study again with U.S.
Data to see if the assumptions that we made using the Australian registry still hold.
So, Hassan, as we talk about these results now and try to put them into context,
in kind of the broader context in order to pitch, what do you think that we
learned from this study?
And how do you put that into context with what's known out there?
(24:35):
And is this something that your group has gotten to the point where you think
that computer-assisted surgery is something that would be cost-effective and
should be broadly accepted?
Or is it something that still requires more study? Where would you kind of put it in context?
I think based on the evidence that we've reviewed and based on this study,
I would advocate for more utilization of computer-assisted total knee arthroplasty.
(25:00):
See i mean and and i think
it's not just providers but also payers they
should i mean the one of the main purposes of this is to tell payers look guys
if you pay for this more people will use it if you pay for this you're going
to save money it's not just better for the patient it's also better for you?
(25:24):
I can tell you with my own experience in robotics, I think that my hospital
was a little bit skeptical at the beginning on how much this was going to cost
and how much I was going to use it.
I think they've had experiences with robots they've gotten at other hospitals
within the network, I'm told, that maybe aren't utilized that much.
And when I jumped in, I jumped in with both feet. I started doing them on 100%
(25:47):
of my primary total knee arthroplasty.
And for the last year and a half. That's really all I've done.
Unless there's some sort of malfunction with the robot, I'm using the robot 100% of the time.
Some of our other surgeons at the same hospital are just using it for more complex cases, et cetera.
And the interesting thing was talking to our industry partners about this.
They're like, wow, we just can't believe you've gone to 100% utilization at the very beginning.
(26:11):
And I stopped and I kind of looked at him weird. I said, well,
why the hell would I not do that?
They're like, almost no. And I was surprised. I didn't know this.
I was surprised to learn that like almost nobody does that, Dr. Banner.
Almost everybody starts by using it on 10, 15% of their patients and isn't using it for everybody.
And for me, I was kind of down on the technology for a long time.
(26:33):
But once I decided I felt like there was an advantage and something to be learned
from it from a research perspective. I felt like it could make me as or more
efficient, which it has.
And it started to see some benefits. And I decided to go with it 100%.
And I kind of wish more surgeons, if you're going to do it, I would encourage
those that are thinking about it.
(26:54):
If you're going to make this change, start doing it.
And once you get comfortable with it, use it all the time and have that become
your new way. Yeah, I think you're doing it because you believe that the technology
is going to improve the outcome of the patient.
I think from an insurer perspective, right now they're paying for computer-assisted
(27:15):
and conventional the same way.
And what we're advocating is that if this is going to save you money on the
long run, Why don't you pay more to the surgeon or the hospital for doing it
as a computer-assisted compared to conventional?
The small amount of payment that's additional in the short run up front will
(27:38):
save you a lot of money on the back end or on the long run in terms of revision rates and other things.
Yeah, I'm glad you said that, Dr. Benner. I'm glad you mentioned the utilization.
And Hassan, I really enjoyed how you and the other authors talked about the
potential cost savings for the payers.
And you mentioned it at the end of the methods as well as the end of the results
section and put it into context that if the utilization of computer-assisted
(28:02):
knee replacement was 60, 80, or 100 percent, and you showed those values that
the payers were able to save.
I think that is a really great point to put in this, especially from a payer
perspective, to see if the utilization was these percentages, what are we saving?
And like you said, if there's some type of incentive that they can offer for
that because they know that the utilization, the higher it gets, the more they save.
(28:25):
Yeah. And especially because there is an upfront cost to robotic surgery,
for example, or computer-assisted surgery. But then if you as the provider feel
that you're getting additional payment for this, you're going to do it more.
Just to give you another example, investing in an MRI, right?
(28:45):
An MRI is like a million dollars or so, right? Why would the hospital buy an MRI?
Because MRI services are covered by insurance, right?
They're willing to pay for it upfront because they know that over time,
they're going to recoup that cost.
And, I mean, we're all sort of humans, we like to make sort of the patient front
(29:12):
and center, we'd like to focus only on the outcomes,
but then there is sort of a financial system around this, right?
And if that financial system or the incentives of that financial systems are
not aligned, they will stand in the way of getting the patient their best outcome.
And what we're trying to do is just to get these financial incentives aligned
(29:35):
with what the surgeon wants to do so that the patient outcomes are optimized.
And we're really thinking about this from strictly, I am anyway,
thinking about it from a strictly American model. And it's not like that anywhere. We had Dr.
Claudette Lejeune from NYU on a few weeks ago talking about the ethics around denying surgery.
(29:56):
And in amongst that, we talked about, as a part of that ethical discussion.
The systems, the countries that have systems with limited resource to where
this is how much you get to spend for your department for a specific amount of time.
And when you're done doing the surgeries you had and run out of money,
you're done until the next cycle starts.
And it's not like that in the United States, but it is in a lot of places around
(30:18):
the world where this kind of information that you're talking about and the cost
that is associated with it has a lot more impact maybe on what will scale that
even in the United States.
But if it's cost savings, you know, Americans ought to be able to think outside
the box of our, you know, of many of our, you know, our tenants of business
that we have to spend money to make money and be able to see the long term.
(30:40):
So I think studies like this are essential and I applaud you for doing it. Thank you very much.
Yorubo, what do you think would be any other take-home points as we start to
wrap up here on what you would want to tell our listeners about cost-effectiveness
as it relates to technology and workplaces? years?
I think cost-effectiveness analysis is an underutilized tool.
(31:03):
I would advocate for always for more cost-effectiveness analysis because they
do inform decisions that are not purely driven by outcomes,
but also driven by the financial incentives and the financial,
yeah, the financial incentives we live with.
And the more we can justify from
(31:25):
a financial incentive or from an economic incentive economic
standpoint that what we're
doing is also saving money i think we
can continue to align the sort
of the clinical objective with the financial objective what do you think the
future is where do you think this is headed if you if you had to pull out your
(31:47):
crystal ball and see when we're you know 10 15 20 years in the future where
are we where do you think we're going to land as we're trying to prognosticate on the economics around.
This issue moving forward yeah i i would like to think that in 15 years all
the procedures will be done sort of with an ai perspective and using sort of
(32:11):
computer-assisted or robotic technology,
but the truth is healthcare moves in a very slow speed.
I don't know if in the next 10 years it's going to catch up with technology, but it's been very slow.
I'll give you an example from my non-orthopedic sort of research.
(32:35):
We've published a nature paper in pediatric surgery, developing an algorithm
that predicts complications two days before they happen.
That's a no-brainer. I mean, it should tell the hospital that they should include
Fitbit data in their electronic medical records, because the value is very high.
(32:56):
You're identifying complications two days before they happen,
so you're intervening much earlier.
Lurie, the hospital that I'm in, and I know many other hospitals still don't
have this Fitbit data in their electronic medical records.
We still haven't figured out how to put this Fitbit on patients and have them
(33:21):
wear them to the post-surgery in a systematic way.
There is, and it's real, there is a disconnect between how quickly technology
is evolving evolving and how slowly healthcare is adopting it.
And if we want to sort of be practical, we need to realize this gap.
(33:44):
Yeah, no doubt about that. I mean, if you're trying to get things to move fast,
going to healthcare systems and government institutions is not exactly a way
to make things go at light speed, as we all know.
So, you know, hopefully we'll keep chipping away at it. And again,
thanks for your contribution to our field and to this specific area of study.
Yeah, just to further that conversation real quick, you know,
(34:05):
Rodney, you mentioned the crystal ball and Hassanian mentioned that the,
you know, in a perfect world in 10 or 15 years, we'd be using AI and robotics
and computer assistant navigation and whatnot.
What can the researchers of the world and the clinicians of the world really
do to speed that up? You know, you talked about this disconnect.
Is that, you know, doing obviously more cost-effective type studies?
(34:29):
And, you know, we were at the academy meeting just earlier this spring,
and I saw more value-based care discussions than I really ever have,
which I think is a good thing because you're talking about potential incentives
and pay-for-performance type metrics,
which I don't know if that's the future or just the idea of value-based care in general.
But my question for you is, how do we speed that process up to connect that
(34:54):
disconnect, if you will?
I'll offer my own perspective on things. I think the more collaboration between
researchers and clinicians.
The more closely the researcher is able to look at the clinical problem,
the more the surgeon is open to collaborating with the researcher.
(35:14):
I think more collaboration means that we get to the solution faster.
Great stuff. So, you know, I think that kind of puts a bow on this topic.
And thank you so much for taking some time out of your night to discuss this
with us. It's been really educational for Scott and I, and hopefully our listeners as well.
And keep up the good work. I'll be looking for future studies if you're named
on them. So thank you very much.
(35:36):
Okay. Pleasure. Very good. Well, check out our previous content.
Other than this episode, if you haven't already, we have 40 plus episodes.
Leave us a five-star review and let those that come behind you know about our
previous content and what you liked.
Check us out on social media at the SKC Podcast, Twitter and Instagram,
and our Facebook and YouTube pages as well.
And we'll see you next time on the Showburning Center Podcast.
(35:57):
Music.
Music.
(00:12):
This is Dr. Benner here for another episode and some more new content.
Another JBJS article that we're going to be talking about tonight.
And we have another author from one of those articles on tonight.
So we'll introduce our guests in just a minute. If you want to find us on social
media, you can find us on Twitter and Instagram at the SKC Podcast.
We have a YouTube and Facebook page for the Shelbourne East Center Podcast.
(00:32):
If you'd like to email us, you can email us at theskcpodcast at gmail.com.
If you like what you've heard for this episode or any of the other ones,
leave us a five star review and a comment for those that come behind you.
And also check out our previous content.
We have over 40 episodes about new topics, and we'd love it if you'd go back
and listen to any of those.
Specifically last week was a great episode. We had a true leader in the field.
(00:53):
We had Dr. Liza Aaron from the University of Minnesota, and we had a great conversation
regarding and centered around the treatment of Patel for moral instability.
And she did a tremendous job. It was a great conversation. She has such great
historical perspectives.
She's been doing this for a long time, working with the athletes at the University
of Minnesota and elsewhere.
And she did a tremendous job discussing the exam, how to take care of these
(01:17):
patients, as well as some surgical techniques for the patellofemoral instability patients.
So go ahead and check out last week's episode to check out the patellofemoral
episode from Dr. Liza Aaron.
Tonight's guest is Hassan Gomrari. He is an associate professor at the Orthopedic
Surgery Department at the University of Alabama at Birmingham.
So he just joined UAB just a couple
(01:38):
of months ago. He is the Vice Chair of Research and Innovation at UAB.
He's also the Associate Director at CAMBAC, which stands for Comprehensive Arthritis,
Musculoskeletal Bone, and Autoimmunity Center.
And we're going to be talking to him tonight about a study that was recently
published in the Journal of Bone and Joint Surgery titled, The Cost-Effectiveness
of Computer-Assisted compared with conventional total knee arthroplasty,
(02:02):
a payer's perspective. So, Dr.
Gomorawi, thank you very much for joining us, and we're happy that you've joined
us on the podcast tonight.
Yep, thank you for having me. Very good. Well, tell us a little bit about your background.
How did you get into this line of work, and how did you, you know,
you're just telling us off-air a little bit about joining this new opportunity
at UAB, and we're just curious about what your background was and how you got
(02:25):
to this position. position?
Yeah, I have a slightly different sort of background than what people would
usually be thinking about how I came to become an orthopedic health services researcher.
When I was doing my master's in public health at the American University of
(02:45):
Beirut, I really wanted to become a,
a pharmaceutical economist and i was doing this study where in lebanon generic drugs are not.
Used they only use brand name drugs and so we did a study comparing generics to,
(03:05):
brand names and the cost savings and i was mind blown by how much savings our
economy could save by using these drugs and so i wanted to be a pharmaceutical economist this.
Applied for the PhD program at the University of Minnesota, got into the program.
Actually did almost a thesis around pharmaceutical economics, didn't work out.
(03:31):
I got this research assistantship with an orthopedic surgeon at the University of Minnesota.
He was doing a multi-center revision neuroplacement study, and I became the
research coordinator for that study, learned about patient-reported outcomes,
got really excited about that.
(03:53):
And that's sort of how I got into orthopedics.
I realized very quickly that there are very few people who know health services
research and also know orthopedic outcomes.
And so I realized quickly that
I could make a big dent in orthopedic outcomes if I get into that field.
(04:14):
And I made the shift from pharmaceutical economics to orthopedic outcomes research.
The nice thing about that, although it was really painful at the time,
was that I was able to act as an outcomes researcher, but also as an economist at the same time.
So I could look at the same problem with multiple lenses.
(04:39):
And then after that, I got the first faculty position at at the renowned HSS
and Weill Cornell Medical College and then was recruited to Northwestern for another few years.
And then a few months ago, UAB made me an offer that I could not say no to. And here I am.
(05:00):
Very good. Well, I appreciate your coming on tonight and an interesting background.
You know, we're getting a lot of economic pressure in orthopedics,
as in all of medicine, to try to get costs down, to try to be cost effective.
And at the same time, there's an explosion of technology in orthopedics as well.
Wearable technology, robotics, computer-assisted navigation,
a lot of talk about AI at meetings and what the future is going to be with artificial
(05:24):
intelligence, et cetera.
And it's an interesting dichotomy to have the micro-level stuff from at home
where we're all getting shaken down for cost savings and then going to meetings
and just hearing about just a broad expansion of technological resources in our field.
So I think it's an interesting space that you inhabit to talk about the economics
(05:49):
around this and be able to understand the outcomes because not everybody can do that.
So, you know, how many people are really looking at these things in quite the same way as you?
How many of you are there out there that are looking at the economics and the
outcomes and trying to put all that together in order to make some real dents
(06:10):
in a couple different directions that orthopedic surgeons and hospital systems are trying to go?
Yeah, I don't know the universe of people who do this, but I know that there are few.
Because every time I go to JBJS or some other orthopedic journal with an economic
analysis, it's more likely to be accepted than not.
(06:32):
And so I think that the field is hungry for economic evaluations that do evaluate
these technologies and estimate the added value to the economy of using these new technologies.
It's interesting that you've mentioned sort of technology because outside of orthopedics,
I also use wearable devices on pediatric surgical patients to try to predict
(07:00):
complications using the Fitbit data.
I do agree. I think you have a fascinating background. I'm curious,
as you went from pharmaceutical economics to more the orthopedic side,
did you see any parallels with that when you were doing the study on the generic drugs?
And as you made the way to starting to look at this from an orthopedic lens,
did you notice there were big similarities or big differences between the two?
(07:23):
It's not so much the similarities in the content, but more the fact that,
for For example, when people look, when surgeons look at joint replacement,
they only, or most of them, I would say, only look at the clinical side of things.
And so, but in the bigger context of things,
(07:45):
joint replacements, all of a sudden, like almost overnight, became this very
highly utilized procedure that Medicare now thinks of it as a major sort of cost center,
right, almost, and they want to do something about it.
And so when you're looking at genetic drugs saving the healthcare system money,
(08:09):
now we're looking at joint replacement and we're trying to figure out ways to
make that procedure save money.
One thing that in my research I've looked at, and I think Dr.
Benner would not totally agree with me, is the whole concept of appropriateness
of joint replacement, which is sort of let's find an objective metric to say,
(08:34):
these people shouldn't be having surgery.
In the policy arena, they're saying, you guys do whatever you want.
You can do the surgery. We're just going to try to lower the cost of the procedure itself.
And my approach was, no, let's try to reduce the number of procedures being
(08:55):
done if a procedure is not appropriate.
I agree with you 100%. I couldn't agree more. You know, because we are a knee-only
clinic, we have knee physical therapists that work in our office.
And for those listening, you can check out some of our previous content to listen
to our non-surgical treatment of knee arthritis talks that we had,
which we covered in a lot of detail.
(09:15):
And the reason is because we're trying a lot at our office to keep people out
of the operating room, which I know is not something that you hear a lot of surgeons say.
A lot of surgeons are saying, do I need an operation? Do you need an operation? Yes or no?
And if the answer is no, best of luck. Go find something that you can do.
You know, here's a couple of things. I think here's a medicine you can try.
Here's an injection I can give. Whenever you're ready to to have surgery,
(09:38):
just come back and let me know.
And our office works the complete opposite of that. We're always trying to think
of what can we do to try to make you better non-surgically?
How can we keep you out of the operating room?
Because it's interesting when you go to meetings, they talk about how our system
is going to be overwhelmed with the number of knee replacements that we have
to do and hip replacements that we have to do.
(10:00):
And yet, everybody's talking about about what do we do to be able to handle
the amount of surgeries that we have to do.
Very few people, if any, are talking about how do we avoid surgery because surgeons
don't want to avoid surgery.
Obviously, our compensation or how busy we are is all tied to the amount of procedures that we do.
That's a whole other direction we could go that you could probably talk about
(10:21):
as well a lot about is how that plays out with pressures from compensation being
directly tied to procedures and how that.
Potentially affects our decision making a lot but but the point is that you
know i agree with you i think that one of the ways that we handle the economics
around this particular problem and specifically you know do we have enough bandwidth
(10:45):
to handle all the arthritis and all the surgeries that we have to do is how
the hell do we find out a way to not do surgery on everybody yep.
Absolutely yeah totally different way of looking at it and probably a discussion
for another day but but interesting perspective that you have there uh you know
let's talk a little bit about the study that we're here to talk about tonight,
where you compared the cost-effectiveness of conventional and computer-assisted
(11:07):
total knee arthroplasty.
Tell us about how you became involved in that specific topic and this specific
study. What was the genesis of this paper?
Yeah, this paper is, I think, the third paper we published on the topic.
The first paper was just, actually, the fourth paper.
The first paper was just a review of the literature, and And it was a systematic review.
(11:33):
We looked at all the published literature, and we found that more or less computer-assisted
was associated with better outcomes.
And then I decided to start analyzing large databases.
I analyzed data from New York and California and Florida, and we looked at data over a 10-year period.
(11:57):
We saw that there was an increase in computer assisted, but the increase is very shy, right?
Or over that period, the utilization increased from 5% of all near placements to about 10%.
So although you'd say it's 100% sort of increase.
(12:17):
Out of the sort of bigger pie, it's still a very small percentage.
We also published another study, a very recent one, where we looked at patients from New York State.
We took everybody, and then we compared computer-assisted versus conventional.
And we found that the outcomes of computer-assisted were much better than those for conventional.
(12:39):
And so in my mind, I was thinking to myself, there is this procedure that produces
better outcomes, but then its utilization is very low.
And what are the drivers of that?
And so one way that I wanted to approach this was to say, are there sort of financial incentives?
(13:02):
Are the financial incentives playing into this? And that's how we did this cost-effectiveness study.
Yeah, I think my general impression is, as we talked about off-air again,
I'm much more into robotic-assisted surgery as opposed to computer navigation,
and I don't think robotics isn't necessarily akin to this particular paper.
(13:23):
Just correct me if I'm wrong.
That's right. This is just not robots.
Yeah, it doesn't include any robotics. Yeah, but I assume a lot of common things
seem to be there in the literature that I think people agree that we can get
better with alignment using technological advances to help do our surgery,
that our chances of having outlier alignment are less if we use some sort of
(13:47):
technological advancement to do the surgery.
I think that is settled science that it does improve alignment outcomes.
I think it is equally that I shouldn't say equally settled science I used to
think that but I think more as it as more data comes out it's a it's at best
uncertain whether or not this really gives us. A couple of.
(14:08):
An outcome measure an outcome measure
improvement for our patients i think that it probably does
the but you know last meeting we went to stop i sat
in a couple sessions about robotics versus standard instrumentation and saw
side by side you know talk after talk studies saying that it made no difference
there was no advantage to robotics and technology and then right behind it one
(14:29):
that said there was so you know and especially as we've started to add in soft
tissue balancing as well as alignment,
for me, that's been a differentiator.
For me, that kind of pushed me over to eventually now doing it.
And now I've done it for about a year and a half, and I've probably done 300
or 400 robotic cases, then I probably won't go back.
So I think it's definitely a controversial thing, and you seem pretty certain
(14:53):
that the data that you've looked at shows some specific advantages,
while others, of course, say that that's not necessarily the case.
So tell us a little bit about, you know, your previous studies, I guess.
I'll be honest, I haven't read your previous studies, just this most recent ones, on what you found.
So, the previous study that compared outcomes found that the in-hospital complications
(15:15):
were lower, much lower for computer-assisted procedures.
And so, when we did the study, the economic study, we made a few assumptions.
One assumption was that these two procedures, if you do it computer-assisted
or not, the quality of life or the PROs are the same, right?
(15:38):
That it's not producing anything better in terms of functional outcomes.
We also did the study from a payer's perspective.
And I think that's the innovation mostly of the study.
The one who's paying for this is the one who's going to drive this.
And there's a lot of prior literature from other procedures that show that if
(16:02):
insurance covers something.
More people will use it. No doubt about that.
And there's ample evidence from the cardiac surgery literature and other procedures
where if insurance covers it, more people will start doing it.
And so I think that's one innovation in this study that hasn't been talked about before.
(16:25):
The other thing is that we recognize that there are two types of patients.
There are the elderly patients who are Medicare patients, and these become Medicare
patients, and they're insured for life.
And so Medicare incentives are to improve your outcomes for the long run, right?
Versus commercial insurance or something like Blue Cross Blue Shield or similar
(16:51):
types of insurers, they cover people for a period of three to ten years.
And so the time horizon there is different. And so the incentives are different.
These insurers focus mostly on short-term benefits, right?
They don't care if you get cancer in 15 years, right?
But they do care if you're insured by them and you're going to get diabetes
(17:16):
in the next two years or a heart attack in the next two years.
So the way we modeled them, we created two different models.
And so we modeled with a short-term perspective and a model with a lifetime perspective.
The other thing is for Medicare too, we said that there are certain patients
(17:37):
who are covered under a bundled payment arrangement, and there are some who
are covered under a fee-for-service arrangement.
And so we did the same modeling under different scenarios, scenarios and in
all scenarios it showed that the computer.
Was more cost-effective than the conventional. And so, regardless of how you
(18:02):
turn it around, it still shows that there is a benefit to computer-assisted surgery.
Now, Hasan, when you're talking about the genesis of this study,
and a lot of it really stemmed from what sounds like your previous work,
and getting into the methodology of this study, now that you've described those two care models,
can you take just a couple minutes and describe more of the methodology,
(18:23):
especially as it pertains to this Markov model.
I know this is a very interesting way to look at the cost effectiveness and
the different scenarios.
So I know that was a big part of the methodology here. I'm looking specifically
at figure one for those that can go back and look at this JBJS article.
So how did you go about that from a statistical standpoint within the methods?
(18:45):
So Markov modeling is a purely hypothetical theoretical exercise,
right? What we do in these models is that we try to mimic the clinical course
of a patient over their lifetime.
So let me give you an example. A patient has knee replacements.
(19:05):
They have a chance of a complication or no complication.
After the complication, they could get better or they could have further complications.
Or the complication could lead to a revision. revision, right?
They could go for a few years and then have a revision.
And so these Markov models are interesting in the sense that they try to mimic the clinical course.
(19:30):
Very closely. And then we use the literature to try to then,
for each sort of what we call a node, which is a probability or,
yeah, a probability node,
which is like, say, what are your chances of having a complication?
In the literature, there's somebody who's done a study using Medicare claims,
(19:52):
for example, and they found that probability of PE is 0.2%. So we use that estimate
and we put it into the model.
So we're trying to create a clinical course for each event in that clinical course.
We're looking at the literature and finding the estimate that we think is the
(20:12):
best, is the most reasonable estimate.
And then after that, we estimate that model.
And it's sort of complicated, but what it does is that it goes through these
Markov models, goes through a repeated cycle of events until the patient dies.
(20:33):
So it could go for 40, 50, 60 years until the hypothetical patient dies.
And then it rolls back and says, over these 60 years, how many quality of life
measures does this patient get and how much cost did this patient incur.
(20:54):
And then we compare the treatment options based on the course of the patient's lifetime.
That seems a little technical, sorry. No, that was very helpful.
That's what Markov models are all about.
Yeah, and I find those models very interesting. At least in my next question,
one of the big outcome parameters you were looking at were the quality-adjusted life years.
(21:18):
And I know you mentioned that when you run this Markov model and you run through
these thousands of simulations and you can come up and determine the effectiveness.
And that was a big part of the tables that you had.
So when you're comparing the effectiveness and you're looking at those quality
life years, and you're comparing here with 0.82, 0.749,
can you explain how that was determined as it relates to the difference between
(21:42):
computer navigation or computer-assisted and conventional TKs? Yeah.
So just to simplify the quality adjusted life here, it's a year,
but if your quality of life during that year is lower than what we consider as optimal,
then you're getting less than a one unit for that year.
(22:02):
And so if you're living with a lot of disability, your quality adjusted life
here is like, I don't know, 0.6, 0.5.
Some people with like cancer have like 0.4. And if you die, your quality goes
to zero during that year.
And so this is sort of a measure that has been developed primarily because they
(22:25):
wanted one measure that can compare treatment across diseases.
So this is sort of a much bigger conversation about prioritizing treatment.
So things like what happened in, for example,
(22:47):
England at one point in time where they decided that they want to look at all
the treatment options and only pay for those that have provided provide the
highest quality of life, the highest qualities, right?
And so we are comparing cancer treatment with total joint replacement,
with vaccines, with other things.
(23:08):
In here, what we've decided to do for these, as I said, we've assumed that these two procedures,
provide the same quality of life, that there's no functional benefit to computer-assisted,
Although, I think there is ample literature out there that shows that computer-assisted
(23:28):
results in better alignment.
So over the long run, you're going to have less loosening, less rates of revision.
But the evidence that's right now is very controversial.
And the only...
Data that we found that has long-term follow-up on these patients is an Australian
joint replacement registry.
(23:50):
And that's where we got our estimates for the difference between revision rates
for computer-assisted and conventional.
And even for that, I mean, the revision rates are not a lot,
just to be very frank about it.
We need more registries from the U.S. to show us this data. I think there is
(24:11):
reason to do this study again with U.S.
Data to see if the assumptions that we made using the Australian registry still hold.
So, Hassan, as we talk about these results now and try to put them into context,
in kind of the broader context in order to pitch, what do you think that we
learned from this study?
And how do you put that into context with what's known out there?
(24:35):
And is this something that your group has gotten to the point where you think
that computer-assisted surgery is something that would be cost-effective and
should be broadly accepted?
Or is it something that still requires more study? Where would you kind of put it in context?
I think based on the evidence that we've reviewed and based on this study,
I would advocate for more utilization of computer-assisted total knee arthroplasty.
(25:00):
See i mean and and i think
it's not just providers but also payers they
should i mean the one of the main purposes of this is to tell payers look guys
if you pay for this more people will use it if you pay for this you're going
to save money it's not just better for the patient it's also better for you?
(25:24):
I can tell you with my own experience in robotics, I think that my hospital
was a little bit skeptical at the beginning on how much this was going to cost
and how much I was going to use it.
I think they've had experiences with robots they've gotten at other hospitals
within the network, I'm told, that maybe aren't utilized that much.
And when I jumped in, I jumped in with both feet. I started doing them on 100%
(25:47):
of my primary total knee arthroplasty.
And for the last year and a half. That's really all I've done.
Unless there's some sort of malfunction with the robot, I'm using the robot 100% of the time.
Some of our other surgeons at the same hospital are just using it for more complex cases, et cetera.
And the interesting thing was talking to our industry partners about this.
They're like, wow, we just can't believe you've gone to 100% utilization at the very beginning.
(26:11):
And I stopped and I kind of looked at him weird. I said, well,
why the hell would I not do that?
They're like, almost no. And I was surprised. I didn't know this.
I was surprised to learn that like almost nobody does that, Dr. Banner.
Almost everybody starts by using it on 10, 15% of their patients and isn't using it for everybody.
And for me, I was kind of down on the technology for a long time.
(26:33):
But once I decided I felt like there was an advantage and something to be learned
from it from a research perspective. I felt like it could make me as or more
efficient, which it has.
And it started to see some benefits. And I decided to go with it 100%.
And I kind of wish more surgeons, if you're going to do it, I would encourage
those that are thinking about it.
(26:54):
If you're going to make this change, start doing it.
And once you get comfortable with it, use it all the time and have that become
your new way. Yeah, I think you're doing it because you believe that the technology
is going to improve the outcome of the patient.
I think from an insurer perspective, right now they're paying for computer-assisted
(27:15):
and conventional the same way.
And what we're advocating is that if this is going to save you money on the
long run, Why don't you pay more to the surgeon or the hospital for doing it
as a computer-assisted compared to conventional?
The small amount of payment that's additional in the short run up front will
(27:38):
save you a lot of money on the back end or on the long run in terms of revision rates and other things.
Yeah, I'm glad you said that, Dr. Benner. I'm glad you mentioned the utilization.
And Hassan, I really enjoyed how you and the other authors talked about the
potential cost savings for the payers.
And you mentioned it at the end of the methods as well as the end of the results
section and put it into context that if the utilization of computer-assisted
(28:02):
knee replacement was 60, 80, or 100 percent, and you showed those values that
the payers were able to save.
I think that is a really great point to put in this, especially from a payer
perspective, to see if the utilization was these percentages, what are we saving?
And like you said, if there's some type of incentive that they can offer for
that because they know that the utilization, the higher it gets, the more they save.
(28:25):
Yeah. And especially because there is an upfront cost to robotic surgery,
for example, or computer-assisted surgery. But then if you as the provider feel
that you're getting additional payment for this, you're going to do it more.
Just to give you another example, investing in an MRI, right?
(28:45):
An MRI is like a million dollars or so, right? Why would the hospital buy an MRI?
Because MRI services are covered by insurance, right?
They're willing to pay for it upfront because they know that over time,
they're going to recoup that cost.
And, I mean, we're all sort of humans, we like to make sort of the patient front
(29:12):
and center, we'd like to focus only on the outcomes,
but then there is sort of a financial system around this, right?
And if that financial system or the incentives of that financial systems are
not aligned, they will stand in the way of getting the patient their best outcome.
And what we're trying to do is just to get these financial incentives aligned
(29:35):
with what the surgeon wants to do so that the patient outcomes are optimized.
And we're really thinking about this from strictly, I am anyway,
thinking about it from a strictly American model. And it's not like that anywhere. We had Dr.
Claudette Lejeune from NYU on a few weeks ago talking about the ethics around denying surgery.
(29:56):
And in amongst that, we talked about, as a part of that ethical discussion.
The systems, the countries that have systems with limited resource to where
this is how much you get to spend for your department for a specific amount of time.
And when you're done doing the surgeries you had and run out of money,
you're done until the next cycle starts.
And it's not like that in the United States, but it is in a lot of places around
(30:18):
the world where this kind of information that you're talking about and the cost
that is associated with it has a lot more impact maybe on what will scale that
even in the United States.
But if it's cost savings, you know, Americans ought to be able to think outside
the box of our, you know, of many of our, you know, our tenants of business
that we have to spend money to make money and be able to see the long term.
(30:40):
So I think studies like this are essential and I applaud you for doing it. Thank you very much.
Yorubo, what do you think would be any other take-home points as we start to
wrap up here on what you would want to tell our listeners about cost-effectiveness
as it relates to technology and workplaces? years?
I think cost-effectiveness analysis is an underutilized tool.
(31:03):
I would advocate for always for more cost-effectiveness analysis because they
do inform decisions that are not purely driven by outcomes,
but also driven by the financial incentives and the financial,
yeah, the financial incentives we live with.
And the more we can justify from
(31:25):
a financial incentive or from an economic incentive economic
standpoint that what we're
doing is also saving money i think we
can continue to align the sort
of the clinical objective with the financial objective what do you think the
future is where do you think this is headed if you if you had to pull out your
(31:47):
crystal ball and see when we're you know 10 15 20 years in the future where
are we where do you think we're going to land as we're trying to prognosticate on the economics around.
This issue moving forward yeah i i would like to think that in 15 years all
the procedures will be done sort of with an ai perspective and using sort of
(32:11):
computer-assisted or robotic technology,
but the truth is healthcare moves in a very slow speed.
I don't know if in the next 10 years it's going to catch up with technology, but it's been very slow.
I'll give you an example from my non-orthopedic sort of research.
(32:35):
We've published a nature paper in pediatric surgery, developing an algorithm
that predicts complications two days before they happen.
That's a no-brainer. I mean, it should tell the hospital that they should include
Fitbit data in their electronic medical records, because the value is very high.
(32:56):
You're identifying complications two days before they happen,
so you're intervening much earlier.
Lurie, the hospital that I'm in, and I know many other hospitals still don't
have this Fitbit data in their electronic medical records.
We still haven't figured out how to put this Fitbit on patients and have them
(33:21):
wear them to the post-surgery in a systematic way.
There is, and it's real, there is a disconnect between how quickly technology
is evolving evolving and how slowly healthcare is adopting it.
And if we want to sort of be practical, we need to realize this gap.
(33:44):
Yeah, no doubt about that. I mean, if you're trying to get things to move fast,
going to healthcare systems and government institutions is not exactly a way
to make things go at light speed, as we all know.
So, you know, hopefully we'll keep chipping away at it. And again,
thanks for your contribution to our field and to this specific area of study.
Yeah, just to further that conversation real quick, you know,
(34:05):
Rodney, you mentioned the crystal ball and Hassanian mentioned that the,
you know, in a perfect world in 10 or 15 years, we'd be using AI and robotics
and computer assistant navigation and whatnot.
What can the researchers of the world and the clinicians of the world really
do to speed that up? You know, you talked about this disconnect.
Is that, you know, doing obviously more cost-effective type studies?
(34:29):
And, you know, we were at the academy meeting just earlier this spring,
and I saw more value-based care discussions than I really ever have,
which I think is a good thing because you're talking about potential incentives
and pay-for-performance type metrics,
which I don't know if that's the future or just the idea of value-based care in general.
But my question for you is, how do we speed that process up to connect that
(34:54):
disconnect, if you will?
I'll offer my own perspective on things. I think the more collaboration between
researchers and clinicians.
The more closely the researcher is able to look at the clinical problem,
the more the surgeon is open to collaborating with the researcher.
(35:14):
I think more collaboration means that we get to the solution faster.
Great stuff. So, you know, I think that kind of puts a bow on this topic.
And thank you so much for taking some time out of your night to discuss this
with us. It's been really educational for Scott and I, and hopefully our listeners as well.
And keep up the good work. I'll be looking for future studies if you're named
on them. So thank you very much.
(35:36):
Okay. Pleasure. Very good. Well, check out our previous content.
Other than this episode, if you haven't already, we have 40 plus episodes.
Leave us a five-star review and let those that come behind you know about our
previous content and what you liked.
Check us out on social media at the SKC Podcast, Twitter and Instagram,
and our Facebook and YouTube pages as well.
And we'll see you next time on the Showburning Center Podcast.
(35:57):
Music.
Popular Podcasts
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.