March 26, 2025 • 48 mins
We asked Chad Starkey about calculating injury risk/injury rate, how ATs could use this data in their practice, and the role epidemiology plays in sports medicine.
Timestamps
(4:40) Epidemiology and Athletic Training
(12:15) What data can the AT look at to calculate injury rate/risk
(13:58) Difference between injury risk and injury rate
(15:21) How comfortable does the AT need to be with tech to calculate injury rate/risk
(16:10) Using this data for stakeholders
(18:51) Where can the AT start to collect data
(22:33) Using published epidemiological studies
(29:50) How can an AT learn more about epidemiology
(31:17) How can ATs use the data they collect
(36:00) What can the AT do if they have low amount of numbers to run injury stats
Action Item: What can an AT do today that can change their practice?
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-Sandy & Randy
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
Hey, this is Sandy. And Randy?
And we're here on at Corner. Being an athlete trainer comes
with ups and downs and we're here to showcase it all.
Join us as we share our world insports medicine.
Welcome back to another episode of At Corner Happy last week of
National Athletic Training Month.
(00:23):
And boy, do we have something soexciting in store for you guys
today. Yes, we have Chad Starkey
talking about epidemiology. So fun fact, Chad actually did
not know what we were going to talk about before we just jumped
into this episode. He actually said, hey, it's more
authentic if if we just go, I could talk about anything, which
(00:45):
if that could, if that shows youjust a little piece of how
awesome, inspiring, amazing thisman is.
Yeah, absolutely, for sure. So Chad Starkey is a professor
and the chair of Department of Athletic Training at Ohio
University. He also serves as the director
of Ohio University's online DAT program and their MSAT program.
(01:07):
Which the DAT program is where we had the luxury of meeting
Chad and that's actually also where we, the two of us have
taken a class from Chad about epidemiology and injury risk,
injury rates and all that. Chad is a graduate of West
Virginia University. He received his master's and
(01:28):
doctoral degrees from Ohio University.
He has served as a Commissioner for the Commission of
Accreditation of Athletic Training Education, on the Board
of Directors for the Board of Certification, and as Chair of
the Education Council of the National Athletic Trainers
Association. From 1986 through 2018, he
provided epidemiological services to the MBA and he has
(01:52):
authored several textbooks focused on sports medicine,
orthopedic diagnosis, and therapeutic modalities.
Which, by the way, I'm pretty sure we all have at least one of
those textbooks. Yes.
And he's served as a Co editor for the for four editions of
Taber's Cyclopedic Medical Dictionary.
(02:13):
Yeah, honestly, epidemiology is kind of a scary word.
I feel like if you don't know, like, it's a big scary word if
you don't really, you know, knowanything about it.
But hopefully after you listen to this and you listen to Chad,
hopefully it's a little bit lessscary how?
And especially after you realizehow much data we have as
athletic trainers, even through everyday documentation.
(02:37):
You ready to get this started right?
Let's do it. All right, so we figured, Chad,
you'd probably really love love to start off with some cryo
Breakers. We figured that would be right
up your alley. So one of our first ones that we
got for you is what is your athletic training muse?
This is a modality rehab tool, tape, braces, etcetera.
(03:00):
Any tool of the trade that represents you.
All of those really bad icons for our profession.
If I were to have a muse, it would be probably a computer or
a brain. That seriously is perfect for
(03:22):
you and perfect for what we're going to talk about.
What, But I mean, I, I get, I don't know what I'm going to,
to, what we're going to talk about, but we, and it's usually
based on the shortage of athletic training trainers or
(03:44):
the, the, the lack of staffing. We tend to go into this
autopilot cookbook treat everybody that this without
sitting down and problem solvingeach patient that we see.
Yeah, I hear you. I, I, I think, yeah, I get when
(04:05):
you get really busy, it's hard to sometimes it's easier to fall
back on it. Well, I've done this before.
We'll keep doing that. I do have to say, I think brain
is probably the first time we'vehad that one.
Yeah. It's the foundation.
But you can teach an 8 year old to tape an ankle, right?
(04:25):
Yeah, that's true. Yeah, that's very true.
We we way over use ice. Mm hmm.
For sure. Well, if you haven't guessed
already, we are talking about epidemiology.
So if you can give us a story, experience, case study,
something that you would like tostart us off with about
(04:47):
epidemiology and athletic trainers, sure.
I excuse me, I just hit puberty nine O 9 Eastern Daylight Time.
I need to market my calendar When when we talk about sports
(05:08):
epidemiology, it's really a dumbing down or almost a
bastardization of what legitimate I I shouldn't what
public health epidemiologists dowe all remember the pandemic and
all the epidemiologists and trying to find that bat that
(05:30):
started everything. We use some of those principles
to again make informed decision decisions regarding patient
care. It can also be extended to
(05:51):
resource allocation, and in thiscase, resources are you your
staff? How are you?
How and where are you going to spend your time based on the
implied risk of the event? What are some things that like
(06:13):
within that kind of realm of epidemiology that the Athai
Turner would be looking at? So you already kind of talked
about like possibly injury risk.What are some other elements of
that that a TS could use or could calculate?
Well, ideally an EMR should be able to calculate all this for
you. Most of them don't, but boy, it
(06:38):
would be really great to if you could push a button and see a
change in your injury rates overtime to identify differences
between any two groups, be it sports or positions within a
(06:59):
sport. Those types of data points will
help people make better databasedecisions.
Chad, if you had a perfect EMR, what would you have it track?
(07:21):
I am going to stand up. And we got the theme of this one
right here. Yeah, it it's funny how over
time your history kind of forgets and most of the people
watching this podcast will have no idea what that means.
(07:48):
Let Alfie help. And then let me turn it around
like that. Sports systems, Sports medicine
software. When it back in 1983, this thing
(08:09):
was developed, called the personal computer.
I took out a student loan to buyan IBMPC just because I'm a nerd
and I, I, I like that kind of stuff.
(08:30):
I taught myself how to program and I built this really bad
injury reporting system medical records package.
I sent it to a friend of mine who actually was an orthopedic
surgeon. And the thing about it was it
(08:51):
said body part, then you had to go to a book and type in a code
and he goes, that's the stupidest thing I've ever seen
in my life. Why do you why do you have it
here? And then in a book I would may
or may not have been at a local establishment and I may or not,
(09:15):
may or may or not have been playing Pac-Man.
And I, I'm dead serious. I'm playing Pac-Man and I'm
using this thing to move Pac-Manaround the board.
And then it dawned on me that ifI listed the body parts on the
screen and used the cursor to track them down, that gets rid
(09:41):
of the the book. So that became software package
named Alfie. Where did the name Alfie come
from in Elvis Costello? So.
Oh. There you go. the IT was the
(10:04):
first commercially successful sports medicine medical records
package. I was running it out of my
basement. I'd be laying on the the couch
watching the Flintstones take a call and make a big chunk of
(10:25):
change there. Kramer products ended up buying
that buying the rights to it. But in that it would give you
all you hit a report section andit would give you your pie
charts of OK, this is your injury distribution by whatever
(10:48):
your dependent variable is. And that in turn led me to
working with the NBA to standardize and consolidate
their medical records. So you know to do the the very
(11:08):
stuff that you all learned in inclass.
Wow, that's really cool, Chad. I'm old.
Is so Alfie is not around anymore.
No, I don't know what happened with with Kramer products.
It was probably around for 10 or12 years.
(11:31):
Oh wow, that's pretty. I do remember.
You know, you all probably aren't old enough to remember
this, but when the 2000s came, there was the Y2K bug and it did
kind of get bitten by the fact that, Gee, I didn't think people
(11:53):
would be using this from for another 17 years.
So some of the fields wouldn't take the the 2000 data, but that
was on them, not me. Yeah, that's crazy.
That's cool. So what sorts of fields are in
there? Are we when we're looking at
epidemiology, are we just looking at body parts?
(12:17):
Are we just looking at athletes,sports?
Like what? What would you recommend for
athletic trainers to look at? It all depends on your question.
It it kind of like a modality. One question doesn't fit all the
(12:37):
circumstances if you want to know, OK, I've got a staff of
three, I've got 72 sports let's take a look at the rate of
injuries during practice. If the the injury rate for
(12:58):
tennis is point OOO one, you probably don't need to have
someone sitting right there at practice.
So, you know, again, it goes back to that human resource
allocation that we discussed right at the beginning.
(13:20):
If your goal is to reduce injuries, you can look at, we'll
use football as an example. Boy, you're finding that your
defensive lineman are really having a lot of shoulder
problems. Is it technique?
(13:40):
Is it strength and conditioning or the lack thereof?
So you identify the problem and then you you use some method to
to correct it. You you discussed a little bit
about rate and and risk. Could you define the differences
between injury rate and injury risk?
(14:04):
Sure, Risk is a probability of an event happening.
It goes from zero to one. Or if you multiply that by 100,
zero to 100. And obviously the closer to 1,
the more probable it is. And, and risk is just simply the
(14:27):
odds of an event happening. So you can do it by player, you
can do it by team. And if one player gets hurt once
when you do your risk calculation, that would be the
same as the person getting injured five times just were you
hurt. Yes.
(14:48):
No rate is more time or exposurebased and that gives you the the
I'm going to use. The word prevalence, which isn't
completely appropriate, is how frequently you would expect
(15:09):
something to happen. So for for calculating like
injury rate, injury risk and kind of using that that data,
how savvy do you have to be likewith the computer to do this?
Is this going to take a lot of like you got to know the innards
of Excel or is this something you can kind of pick up pretty
(15:29):
quickly? In the class you all had, I
believe one of the the first slides was a plus sign, a minus
sign, a division sign, and a multiplication sign.
(15:49):
If you can know, if you know howto do those four functions,
you're 90% of the way to to to most of the things that that you
need to know. For sure.
That's awesome. That's really cool.
So when you're using this data to bring to administrators, how
(16:13):
would you put that in a way thatmakes it digestible for them?
Pictures. OK, I I.
I mean, if you're, if you're looking to an article or if
you're looking at something on the the web and there's all of
(16:37):
these words, but there's a graphthat explains it, Which one are
you going to be more drawn to and which one is going to leave
more of a lasting impact on you for?
Sure. Definitely the pictures.
How far is your drive from home to your work?
(17:02):
10 minutes. For some of us, it's 32 an hour.
OK, so in your 10 minutes or you're 32 an hour, how many
billboards do you go pass? A ton.
Yeah, Randy gets a ton. Tell me, Tell me one of them.
(17:25):
Well, I see a lot of injury attorney billboards and accident
attorney billboards on the way to work.
Next time you drive into work and don't become overly
distracted doing this it It is really really rare to see a
(17:47):
billboard that has more than 7 words on it.
Oh I'm I'm all in now. I want to see this.
I, I, I mean, I could believe that for sure.
And it it's, it's a combination.It's usually the visual that
that draws your attention to it.And then the, the few words put
(18:10):
all that in into context. So your injury attorney lawyers
probably have a big old cigar there in their mouth.
Yes, for sure. It it you know what, it is
usually a picture of themselves.There's one with the dog.
There is the one with the dog, that's right.
(18:31):
The dog is an attorney. It's a very smart maybe.
Maybe a partner? It's a mascot.
Junior associate? Maybe so you kind of alluded to
this as far as just kind of likethe EMR component, but like kind
of what's the easiest way to start collecting this data?
(18:53):
Like sometimes when you hear like calculating injury risk,
injury rate, it seems like theremight be a lot of work to it.
So what's kind of just the easy way to just get going?
A lot of it is going to be dependent on which EMR you use
(19:13):
and you know what, what fields those Emrs collect.
The other thing that some Emrs will do this, others don't you
you'll need to a way to calculate exposures days is the
easiest way to do that. But when I was doing the stuff
(19:40):
with the NBAI had the luxury of being able to say, oh, Sandra
Harris played 732 minutes so far.
Well, there's your denominator, and it's a very precise
denominator. The more general you get, the
(20:00):
more the less applicable your your outcomes are.
So for a sport like basketball, it's a lot easier to calculate
the number of minutes that someone's playing.
But for a sport more like football or soccer, you know,
you don't really have that data as readily available.
(20:20):
How would you go about finding exposures in those?
Sports in in that case you woulduse appearances in the game.
Now, the the problem with doing that is if you 2 are on a soccer
team, you both appear in a game that's one, that's two
exposures, one each. But if Randy plays 30 seconds
(20:47):
and Sandra plays, I don't know how long a soccer game is soccer
matches, but we'll say 45 minutes, you know, they both
count as an exposure, but one exposure's like that the other
ones. So and that's kind of the the
the problem with using larger chunks for for your epic.
(21:14):
Have you ever taken this data toa coach and made any changes?
No, but when I was doing this, remember I was working with the
athletic trainers in the league office.
So we did use data for decision making purposes.
(21:38):
Wow, that's really cool. Especially at at that level of
sport. Like that's really awesome.
And the reason why I haven't is almost my whole career has been
here in geekdom, but I have helped.
(22:00):
It's our athletic training staffdo this in class.
I I try to help you know how to put this stuff together so so
you can use it. For sure.
You know, another thing that I was kind of thinking of is I've
seen a lot of epidemiological studies on just kind of looking
(22:23):
at like injury rates across likelike I've seen some from like
NCAA that looked at cross country injuries over like the
last 10 years. If you're in a place that like,
hey, maybe you just don't have the time to necessarily collect
as much like that exposure data.Is it possible to use the those
epidemiological studies to help kind of decision making or do
(22:45):
you need it still a little more personalized?
You can use large scale epidemiological studies to make
inferences. And in your case, if you're
using cross country, if you findif that 10 year study said,
(23:08):
well, here's the average rate ofinjury in cross country and
you're way up here that that gives you a metric to to say,
you know, at least identify thata problem exists.
For sure. That brings up a really good
(23:29):
point because from even from my football season last year to
this year's season, we had drastically different injury
rates. Even in in position group, it
was significantly more the second season and obviously
there were a lot of factors thatwent into that.
But looking into what a normal injury rate is for some of these
(23:56):
athletes, looking at the first season, it was not really that
the second season was so much more injury prone.
It was, it was really that our, our first year, I mean, we were
all so undefeated and we were, we were the, the, IT really does
make a difference when you are the bigger football players.
And so we really had a low injury rate the first year.
(24:20):
We started out talking about thethe big picture of epidemiology
and, and what you see in the movies in and on TV and stuff.
Finding patient zero and figuring out how something
spreads and trans what the with orthopedic injuries they
(24:43):
obviously are not communicable. Ultimately that boils down to
bad luck. Someone goes in for a layup,
comes down and they have their leg just a little bit out of
(25:07):
position, puts it in the vulnerable spot, there goes the
ACL. So if one of the things that we
need to accept and really one ofthe reasons, primary reasons why
we exist as a profession is thatwhen you have 2300 LB people
(25:32):
running into each other, eventually an injury's going to
happen. For.
Sure. And and you know, there are
certainly the freak injuries that that happened.
There's somebody sitting on the bench and gets hit by a foul
ball in the head and suffers a concussion that you know, bad
(25:56):
things unfortunately do happen and we could not prevent every
injury. Definitely not.
For sure now. Now when I look at my injury
stats, all I'm going to see is astat stat sheet of bad luck.
That's the first thing that's going to pop in my head now.
(26:16):
Oh yeah, the whole concept of being injury prone, yes, there.
Yeah. I can't remember it right now,
but somebody did a a really nicearticle, that research article
that does show that some people just genetically are at an
increased risk of injury. Wow, that is really fascinating.
(26:42):
Yeah. When we genetic cell is a really
big influence, especially we were with ACL injuries.
I was just thinking that this was an internal study that was,
(27:04):
we didn't publish it, but we, weme went through, I probably had
almost 20 years of data at this point.
And I went through and I identified every set of
biological brothers that played in the NBA.
(27:29):
And in every case, if one one ofthe siblings tore an ACL, the
other one did. Wow.
Wow, that's. Interesting.
And if one or if one sibling didnot rupture an ACL, the other
one didn't. So now that that only includes
(27:50):
at the professional level, we didn't, I didn't go back and
look at high school or college, but it was still really an
intriguing fact. And I'll ask why students in the
classroom, how many people here have ruptured an ACL?
(28:11):
Depending on how active the class hands will go up.
And then I'll say, OK, of those that did, who have we who have
you have had a sibling rupture in ACL and not everybody's hands
stays up, but it's like, Oh yeah.
(28:35):
That's interesting. I, I feel like it was, I feel
like this was a quite a few years ago now, but like, I think
it was like a session at NATA orsomething.
They were talking about certain genes and like like a certain up
regulation, down regulation of genes kind of led to or kind of
hinted at possibly being an increased risk of ACL tear.
(28:56):
So yeah, I have heard of that for sure.
Well, just recently one of my athletes tore their ACL and I
said, hey, you know, it was, I believe it was their right leg.
So I was like, well, you're not going to be able to drive.
So I was like, hey, do you have like, can you call your parent
to pick you up? And they're like actually my
parents on on the way to take mybrother to ACL surgery right
(29:18):
now. He.
Boils down, it boils. Down to you get to say thanks
mom and dad. I was like, you guys get to do
rehab together, Yeah. The brothers at rehab together
stay together. So we've kind of hinted at this
(29:42):
again, just kind of like the class that you do teach on this
and you know, we've, we've been like very lucky to actually take
this class, but kind of where can someone kind of learn more
about epidemiology if they're not able to like take a class?
What I would recommend is getting on the Google OR and not
(30:03):
to discriminate if you're a Bingperson, and search Zack Kerr.
Kerr, who is at University of North Carolina Chapel Hill.
He's not an athletic trainer, but he is without a doubt the
(30:28):
most active sports epidemiologist out there.
Now he is is provided so much information to the athletic
training profession regarding sports epidemiology.
He he works with Dataless, who does the the NCAA and the high
(30:50):
school study, does all their statistical analysis.
You know, it's really cool to see this all come together
because as we've talked about before there as an athletic
trainer and in our profession, we do collect so much data.
But it's really what do we do with that rather than it just
(31:13):
sitting in a computer or software somewhere.
How can we actually utilize thatto show our value to help
decrease injury risk to etcetera, etcetera?
And again, this is probably a workload issue.
Mm Hmm. But athletic trainers aren't
(31:35):
always the best at maintaining good records.
And I think that if you take an athletic trainer that works in
the private for profit setting versus you all, there's more.
(31:58):
There's suddenly the demand, theexpectation that those
clinically, these people document everything that they
do, be it the diagnostics or intervention.
But that shows the, the word that shows what, what people are
(32:21):
getting out of it. We, we don't do quite as good of
a job in the quote UN quote traditional setting this we
should. And you know, anytime you
generalize like that, you're generally wrong.
But I I think to the it's an area that I think everybody can
(32:47):
improve it. For sure, yeah.
And you know, that's what I kindof tell my students like when
I'm kind of teaching them the concepts of, of epidemiology and
kind of calculating injury rate is just this like we as athletic
trainers are exposed to so many opportunities to collect data.
(33:07):
And if you're, if you're documenting like your EMR has
like just a ton of data, that isdefinitely usable if you have
the time to do so. And some you have to pull out
manually and some of them depending on what EMR you use
like you can create those reports like you were talking
about. Definitely depends on your
(33:29):
question. AI can be used for good or evil.
I'm working on the evil part, but I I can see in the very near
future you tell your computer Sandra Harris, right?
(33:53):
ACL rupture, blah, blah blah. It'll sort all that.
Put it into the Mr. for you and then a using our data, calculate
the rate of ACL injuries, OK, now calculate that rate male
versus female or football versusbasketball.
(34:15):
So the, the good aspect of AI are, are those type of things
that will make the use of our time more effective.
You don't have to to sit there and and and figure it out
yourself. I was going to say, man, that
(34:37):
would cut down so much time for me.
That would be fantastic. Only if you use it for evil.
I think that kind of leads into if time's a little tight, how
can you analyze the data either with AI, without AI, if you're
(34:58):
like, do we just need to focus on the time to document or like
what advice do you have for athletic trainers who you're
right, the workload is just thatmuch Well.
First of all, we we have the legal obligation to document
(35:19):
this anyway, so. Absolutely.
That that needs to be where youryour emphasis is.
It shouldn't be that challengingtime wise to again if your EMR
is set up for it or you downloaded into Excel to go
(35:41):
through it and and make those calculations for.
Sure. Now some of these the numbers
become a little bit unstable if your N is less than 30.
So are we really limited by thator how do you recommend if you
(36:02):
have like a smaller? That the the the low N is is
most usually effects confidence intervals, so if you have
something with the low end you could use the odds ratio for
relative risk calculations. Nice.
(36:28):
You ready for an action? Yes, I think it's time for this
is Sandra's favorite part because she's all about action
and what can we do right now. So what can an AT do today that
can change their practice? And athletic trainers listening
on their way to work right now, they're going to go into their
into their office and they're going to change something today.
But first of all, I hope they have a nice day.
(36:52):
Keep things in perspective. The one thing we you've heard,
the expression garbage in, garbage out.
The more accurate what you document, both in terms of
detail and being sure that you capture everything, gives you
(37:13):
that foundation of data that youcould use to withdraw later on
for. Sure, I like that.
That's what, again, that's what I try to tell my students.
Like whatever you're getting outof your like EMR or whatever
data you're trying to look up is, is only as good as what's
being put in. So you know, that should kind of
(37:36):
be like your kind of expectationof like if you've put in a lot
into your EMR and a lot into that kind of data usage, like
you should be able to get a lot out of it.
Or if you only put kind of limited like you, it might kind
of limit what you're able to actually pull out of it.
And it was the other thing we spoke about is OK, if when you
(38:00):
identify the body part, if you go leg, that's by the end of the
season, you're going to have a whole lot of leg.
As a matter of fact, I bet you you have twice as many legs as
you have people. And then if you go leg, knee,
you're going to take the end from here down to here and then
(38:23):
you go knee. We'll, we'll, we'll show the PCL
some love here, the PCL. So what you say, if you drill
down too deep it, you're not going to get that end to make
the the really rational conclusion from it.
(38:48):
A lot of this is just the eyeball test too.
If your your your men's team hasone ACL rupture over the last
five years and your women's teamhas 22, you you, you don't need
to take a class to figure out that's not right.
(39:09):
Yeah, yeah, that, you know, that's.
A good way to say in southeast eastern Ohio, that ain't right.
That's a good way of putting it for sure.
There are times you could kind of just look at it and just be
like something weird's going on,yeah.
And then you can take that something weird and build it
into a more scientific hypothesis for sure, but it
(39:36):
takes the weirdo factor to kind of trigger that.
Yeah, that's true. And look at that.
Science started by weird. Weird science.
Yeah, see there. You go.
Finally, a movie reference somebody gets.
(39:58):
Honestly, also talking about just streamlining, 'cause you
kind of brought it, brought it up.
If you just put something in thenotes of your EMR, right, it's
going to be a lot more difficultto pull out later.
But if you use like your drop down features or we created a
sign in on an iPad that goes directly to an Excel file.
(40:18):
So then we can take that data and do whatever we want with
that and we can. Sort of by sport or whatever I
can use that to then put into myEMR.
So really if you, if you find a system that works for you and
you're streamlining, it's going to be a lot easier than looking
in like every SOAP note you've written, like clicking the
person's name, clicking open, clicking notes, clicking the and
(40:41):
then and then reading through and trying to find some piece of
data. If you streamline, streamline
the process, it's going to be a lot easier on you on the back
end to find the time to do all these things.
Yes. A1 day AI.
Yeah. And again, that would be in a
perfect example. OK, take these SOAP notes,
(41:05):
identify the body parts, identify the intervention.
Nice. Our university has some pretty
harsh policies on use of AII. Encourage our students to to use
it. I think that's one thing that
(41:26):
I've kind of noticed is I think I feel like people should at
least get comfortable using it as a tool to kind of help, you
know? And I told tell them when I was
a kid, there was a device that was invented that was going to
destroy humanity as we knew it. That was called the calculator.
(41:51):
People are going to have calculators and they're not
going to know how to do math. Well, no.
Having the calculator just makesthe application of math easier.
You don't have to remember your multiplication tables.
The calculator obviously does that for you.
(42:13):
Then the the teacher would say, yeah, but you're not always
going to have a calculator. Let me see if she's still alive
yet or not. I do remember that argument all
the time. I think math is now much more
usable by more people and it's going to be the same thing with
(42:35):
AI and information. I mean, calculating all this
data without a calculator I can't even imagine.
But I, if you go to like Gemini and you say, OK, I've got 142
athletes, there were seven wristfractures, but calculate the,
(43:02):
the you know, the risk grade, etcetera for it.
It may need more data than my quick little stem there, but it
it can do it for you now. Nice, that's interesting.
That's really cool. I I didn't even think of yeah.
I'm telling you how to cheat formy class now that you're done.
Hey, we're hey, we're already took the class.
(43:23):
We're good. Is this is this not a good time
to bring up that after I did my assignment I used AI to double
check that I made the proper conclusions?
Did you really? I did.
I don't remember that. I'm completely fine with that.
I think she congratulated for that.
(43:44):
I would say it's encouraged. But you still didn't pass.
You mean AI didn't pass? Yeah, I did.
I can develop an AI program to do this and we can call it
(44:07):
ChatGPT you. Heard something?
You heard it here first. Yeah, well, I'm going to retire
from this job here and go do that.
Do I think we just we just had our we just found our first AI
infused ATHI training EMR. Alfie makes a comeback.
(44:34):
What's Alfie's last name? It must start with an I.
No for because IP systems. There we go.
Yeah, IP stood for idiot proof. That's pretty funny.
I like that. Sweet.
(44:55):
So just to wrap things up there,we just talked about some data
that we've turned into value. Like I think in the episode we
we talked about like the sign insheets.
But also, for example, somethingthat I use is my injury report.
So like every day I create an injury report for or every,
(45:16):
every practice day, I should say, I create an injury report
for football. And at the end of the season,
the last two seasons, I've been able to take those because it's
already in an Excel document andI just put them in a new Excel.
And then I'm able to really filter out things and, and
figure out what injuries, what sides of injuries, the positions
(45:41):
and, and just really like whatever I put into it.
Like we've said, an episode is really what you get out of it.
Yeah, for sure. I think that again, that's like
I said during the the interview is that's one of the most
important things that I teach the athletic training students
is like the data you get is onlyas good as like what you put in,
right. So if you're trying to ask a
(46:02):
specific question, right, you got to make sure you have the
data to kind of help you. Or if you're just thought of
that question and you haven't collected that data, now you
know where to start and like, oh, well, here's what I'm
thinking. Here's how I should collect that
data. Yeah, exactly.
So it's a lot more accessible than I think people think, for
sure. It just takes a minute to get
started. And then once, once you really
(46:22):
get started, then you're going to be like, oh, I could look
into this. I could look into this, I could
look into this. Just opens a Pandora box of
data. For real, so if you guys are new
here, we do every episode as either interviews like this one.
We do other episodes as stories from real life athletic trainers
about various topics all around the world, athletic trainers
(46:45):
from all around the world, whichis really exciting.
And then we also do education episodes, which Randy heads and
those ones are worth category ACus.
Thank you so much to athletic training chat and clinically
pressed. If you're interested in looking
at those C us, we actually have a sale running.
We have some free ones, but we also have a sale running through
(47:05):
the end of national Athletic training month.
So you can use code NATM 25 for 25% off those.
C us. There's also still a couple more
days of NATM. So because of that, we are still
running our giveaway if you're listening to this as it comes
out. So enter our giveaway with Medco
to win a Merritt Mueller kit andsome podcast merch.
(47:27):
Super exciting. And then if you're interested in
more Cus, you can also use code 80 corner for $101.00 off
Medbridge. It is a reporting year.
Yes, it is. So if you guys are interested in
sending your stories or just chatting with us, head over to
our Instagram at 80 Corner podcast where you can do a bunch
(47:49):
of the things that I already talked about.
We also have a bunch more links and stuff down below in the
podcast description. So I think that's all my fine
print. Thank you for helping us
showcase athletic training behind the tape.
Bye.
Hey, this is Sandy. And Randy?
And we're here on at Corner. Being an athlete trainer comes
with ups and downs and we're here to showcase it all.
Join us as we share our world insports medicine.
Welcome back to another episode of At Corner Happy last week of
National Athletic Training Month.
(00:23):
And boy, do we have something soexciting in store for you guys
today. Yes, we have Chad Starkey
talking about epidemiology. So fun fact, Chad actually did
not know what we were going to talk about before we just jumped
into this episode. He actually said, hey, it's more
authentic if if we just go, I could talk about anything, which
(00:45):
if that could, if that shows youjust a little piece of how
awesome, inspiring, amazing thisman is.
Yeah, absolutely, for sure. So Chad Starkey is a professor
and the chair of Department of Athletic Training at Ohio
University. He also serves as the director
of Ohio University's online DAT program and their MSAT program.
(01:07):
Which the DAT program is where we had the luxury of meeting
Chad and that's actually also where we, the two of us have
taken a class from Chad about epidemiology and injury risk,
injury rates and all that. Chad is a graduate of West
Virginia University. He received his master's and
(01:28):
doctoral degrees from Ohio University.
He has served as a Commissioner for the Commission of
Accreditation of Athletic Training Education, on the Board
of Directors for the Board of Certification, and as Chair of
the Education Council of the National Athletic Trainers
Association. From 1986 through 2018, he
provided epidemiological services to the MBA and he has
(01:52):
authored several textbooks focused on sports medicine,
orthopedic diagnosis, and therapeutic modalities.
Which, by the way, I'm pretty sure we all have at least one of
those textbooks. Yes.
And he's served as a Co editor for the for four editions of
Taber's Cyclopedic Medical Dictionary.
(02:13):
Yeah, honestly, epidemiology is kind of a scary word.
I feel like if you don't know, like, it's a big scary word if
you don't really, you know, knowanything about it.
But hopefully after you listen to this and you listen to Chad,
hopefully it's a little bit lessscary how?
And especially after you realizehow much data we have as
athletic trainers, even through everyday documentation.
(02:37):
You ready to get this started right?
Let's do it. All right, so we figured, Chad,
you'd probably really love love to start off with some cryo
Breakers. We figured that would be right
up your alley. So one of our first ones that we
got for you is what is your athletic training muse?
This is a modality rehab tool, tape, braces, etcetera.
(03:00):
Any tool of the trade that represents you.
All of those really bad icons for our profession.
If I were to have a muse, it would be probably a computer or
a brain. That seriously is perfect for
(03:22):
you and perfect for what we're going to talk about.
What, But I mean, I, I get, I don't know what I'm going to,
to, what we're going to talk about, but we, and it's usually
based on the shortage of athletic training trainers or
(03:44):
the, the, the lack of staffing. We tend to go into this
autopilot cookbook treat everybody that this without
sitting down and problem solvingeach patient that we see.
Yeah, I hear you. I, I, I think, yeah, I get when
(04:05):
you get really busy, it's hard to sometimes it's easier to fall
back on it. Well, I've done this before.
We'll keep doing that. I do have to say, I think brain
is probably the first time we'vehad that one.
Yeah. It's the foundation.
But you can teach an 8 year old to tape an ankle, right?
(04:25):
Yeah, that's true. Yeah, that's very true.
We we way over use ice. Mm hmm.
For sure. Well, if you haven't guessed
already, we are talking about epidemiology.
So if you can give us a story, experience, case study,
something that you would like tostart us off with about
(04:47):
epidemiology and athletic trainers, sure.
I excuse me, I just hit puberty nine O 9 Eastern Daylight Time.
I need to market my calendar When when we talk about sports
(05:08):
epidemiology, it's really a dumbing down or almost a
bastardization of what legitimate I I shouldn't what
public health epidemiologists dowe all remember the pandemic and
all the epidemiologists and trying to find that bat that
(05:30):
started everything. We use some of those principles
to again make informed decision decisions regarding patient
care. It can also be extended to
(05:51):
resource allocation, and in thiscase, resources are you your
staff? How are you?
How and where are you going to spend your time based on the
implied risk of the event? What are some things that like
(06:13):
within that kind of realm of epidemiology that the Athai
Turner would be looking at? So you already kind of talked
about like possibly injury risk.What are some other elements of
that that a TS could use or could calculate?
Well, ideally an EMR should be able to calculate all this for
you. Most of them don't, but boy, it
(06:38):
would be really great to if you could push a button and see a
change in your injury rates overtime to identify differences
between any two groups, be it sports or positions within a
(06:59):
sport. Those types of data points will
help people make better databasedecisions.
Chad, if you had a perfect EMR, what would you have it track?
(07:21):
I am going to stand up. And we got the theme of this one
right here. Yeah, it it's funny how over
time your history kind of forgets and most of the people
watching this podcast will have no idea what that means.
(07:48):
Let Alfie help. And then let me turn it around
like that. Sports systems, Sports medicine
software. When it back in 1983, this thing
(08:09):
was developed, called the personal computer.
I took out a student loan to buyan IBMPC just because I'm a nerd
and I, I, I like that kind of stuff.
(08:30):
I taught myself how to program and I built this really bad
injury reporting system medical records package.
I sent it to a friend of mine who actually was an orthopedic
surgeon. And the thing about it was it
(08:51):
said body part, then you had to go to a book and type in a code
and he goes, that's the stupidest thing I've ever seen
in my life. Why do you why do you have it
here? And then in a book I would may
or may not have been at a local establishment and I may or not,
(09:15):
may or may or not have been playing Pac-Man.
And I, I'm dead serious. I'm playing Pac-Man and I'm
using this thing to move Pac-Manaround the board.
And then it dawned on me that ifI listed the body parts on the
screen and used the cursor to track them down, that gets rid
(09:41):
of the the book. So that became software package
named Alfie. Where did the name Alfie come
from in Elvis Costello? So.
Oh. There you go. the IT was the
(10:04):
first commercially successful sports medicine medical records
package. I was running it out of my
basement. I'd be laying on the the couch
watching the Flintstones take a call and make a big chunk of
(10:25):
change there. Kramer products ended up buying
that buying the rights to it. But in that it would give you
all you hit a report section andit would give you your pie
charts of OK, this is your injury distribution by whatever
(10:48):
your dependent variable is. And that in turn led me to
working with the NBA to standardize and consolidate
their medical records. So you know to do the the very
(11:08):
stuff that you all learned in inclass.
Wow, that's really cool, Chad. I'm old.
Is so Alfie is not around anymore.
No, I don't know what happened with with Kramer products.
It was probably around for 10 or12 years.
(11:31):
Oh wow, that's pretty. I do remember.
You know, you all probably aren't old enough to remember
this, but when the 2000s came, there was the Y2K bug and it did
kind of get bitten by the fact that, Gee, I didn't think people
(11:53):
would be using this from for another 17 years.
So some of the fields wouldn't take the the 2000 data, but that
was on them, not me. Yeah, that's crazy.
That's cool. So what sorts of fields are in
there? Are we when we're looking at
epidemiology, are we just looking at body parts?
(12:17):
Are we just looking at athletes,sports?
Like what? What would you recommend for
athletic trainers to look at? It all depends on your question.
It it kind of like a modality. One question doesn't fit all the
(12:37):
circumstances if you want to know, OK, I've got a staff of
three, I've got 72 sports let's take a look at the rate of
injuries during practice. If the the injury rate for
(12:58):
tennis is point OOO one, you probably don't need to have
someone sitting right there at practice.
So, you know, again, it goes back to that human resource
allocation that we discussed right at the beginning.
(13:20):
If your goal is to reduce injuries, you can look at, we'll
use football as an example. Boy, you're finding that your
defensive lineman are really having a lot of shoulder
problems. Is it technique?
(13:40):
Is it strength and conditioning or the lack thereof?
So you identify the problem and then you you use some method to
to correct it. You you discussed a little bit
about rate and and risk. Could you define the differences
between injury rate and injury risk?
(14:04):
Sure, Risk is a probability of an event happening.
It goes from zero to one. Or if you multiply that by 100,
zero to 100. And obviously the closer to 1,
the more probable it is. And, and risk is just simply the
(14:27):
odds of an event happening. So you can do it by player, you
can do it by team. And if one player gets hurt once
when you do your risk calculation, that would be the
same as the person getting injured five times just were you
hurt. Yes.
(14:48):
No rate is more time or exposurebased and that gives you the the
I'm going to use. The word prevalence, which isn't
completely appropriate, is how frequently you would expect
(15:09):
something to happen. So for for calculating like
injury rate, injury risk and kind of using that that data,
how savvy do you have to be likewith the computer to do this?
Is this going to take a lot of like you got to know the innards
of Excel or is this something you can kind of pick up pretty
(15:29):
quickly? In the class you all had, I
believe one of the the first slides was a plus sign, a minus
sign, a division sign, and a multiplication sign.
(15:49):
If you can know, if you know howto do those four functions,
you're 90% of the way to to to most of the things that that you
need to know. For sure.
That's awesome. That's really cool.
So when you're using this data to bring to administrators, how
(16:13):
would you put that in a way thatmakes it digestible for them?
Pictures. OK, I I.
I mean, if you're, if you're looking to an article or if
you're looking at something on the the web and there's all of
(16:37):
these words, but there's a graphthat explains it, Which one are
you going to be more drawn to and which one is going to leave
more of a lasting impact on you for?
Sure. Definitely the pictures.
How far is your drive from home to your work?
(17:02):
10 minutes. For some of us, it's 32 an hour.
OK, so in your 10 minutes or you're 32 an hour, how many
billboards do you go pass? A ton.
Yeah, Randy gets a ton. Tell me, Tell me one of them.
(17:25):
Well, I see a lot of injury attorney billboards and accident
attorney billboards on the way to work.
Next time you drive into work and don't become overly
distracted doing this it It is really really rare to see a
(17:47):
billboard that has more than 7 words on it.
Oh I'm I'm all in now. I want to see this.
I, I, I mean, I could believe that for sure.
And it it's, it's a combination.It's usually the visual that
that draws your attention to it.And then the, the few words put
(18:10):
all that in into context. So your injury attorney lawyers
probably have a big old cigar there in their mouth.
Yes, for sure. It it you know what, it is
usually a picture of themselves.There's one with the dog.
There is the one with the dog, that's right.
(18:31):
The dog is an attorney. It's a very smart maybe.
Maybe a partner? It's a mascot.
Junior associate? Maybe so you kind of alluded to
this as far as just kind of likethe EMR component, but like kind
of what's the easiest way to start collecting this data?
(18:53):
Like sometimes when you hear like calculating injury risk,
injury rate, it seems like theremight be a lot of work to it.
So what's kind of just the easy way to just get going?
A lot of it is going to be dependent on which EMR you use
(19:13):
and you know what, what fields those Emrs collect.
The other thing that some Emrs will do this, others don't you
you'll need to a way to calculate exposures days is the
easiest way to do that. But when I was doing the stuff
(19:40):
with the NBAI had the luxury of being able to say, oh, Sandra
Harris played 732 minutes so far.
Well, there's your denominator, and it's a very precise
denominator. The more general you get, the
(20:00):
more the less applicable your your outcomes are.
So for a sport like basketball, it's a lot easier to calculate
the number of minutes that someone's playing.
But for a sport more like football or soccer, you know,
you don't really have that data as readily available.
(20:20):
How would you go about finding exposures in those?
Sports in in that case you woulduse appearances in the game.
Now, the the problem with doing that is if you 2 are on a soccer
team, you both appear in a game that's one, that's two
exposures, one each. But if Randy plays 30 seconds
(20:47):
and Sandra plays, I don't know how long a soccer game is soccer
matches, but we'll say 45 minutes, you know, they both
count as an exposure, but one exposure's like that the other
ones. So and that's kind of the the
the problem with using larger chunks for for your epic.
(21:14):
Have you ever taken this data toa coach and made any changes?
No, but when I was doing this, remember I was working with the
athletic trainers in the league office.
So we did use data for decision making purposes.
(21:38):
Wow, that's really cool. Especially at at that level of
sport. Like that's really awesome.
And the reason why I haven't is almost my whole career has been
here in geekdom, but I have helped.
(22:00):
It's our athletic training staffdo this in class.
I I try to help you know how to put this stuff together so so
you can use it. For sure.
You know, another thing that I was kind of thinking of is I've
seen a lot of epidemiological studies on just kind of looking
(22:23):
at like injury rates across likelike I've seen some from like
NCAA that looked at cross country injuries over like the
last 10 years. If you're in a place that like,
hey, maybe you just don't have the time to necessarily collect
as much like that exposure data.Is it possible to use the those
epidemiological studies to help kind of decision making or do
(22:45):
you need it still a little more personalized?
You can use large scale epidemiological studies to make
inferences. And in your case, if you're
using cross country, if you findif that 10 year study said,
(23:08):
well, here's the average rate ofinjury in cross country and
you're way up here that that gives you a metric to to say,
you know, at least identify thata problem exists.
For sure. That brings up a really good
(23:29):
point because from even from my football season last year to
this year's season, we had drastically different injury
rates. Even in in position group, it
was significantly more the second season and obviously
there were a lot of factors thatwent into that.
But looking into what a normal injury rate is for some of these
(23:56):
athletes, looking at the first season, it was not really that
the second season was so much more injury prone.
It was, it was really that our, our first year, I mean, we were
all so undefeated and we were, we were the, the, IT really does
make a difference when you are the bigger football players.
And so we really had a low injury rate the first year.
(24:20):
We started out talking about thethe big picture of epidemiology
and, and what you see in the movies in and on TV and stuff.
Finding patient zero and figuring out how something
spreads and trans what the with orthopedic injuries they
(24:43):
obviously are not communicable. Ultimately that boils down to
bad luck. Someone goes in for a layup,
comes down and they have their leg just a little bit out of
(25:07):
position, puts it in the vulnerable spot, there goes the
ACL. So if one of the things that we
need to accept and really one ofthe reasons, primary reasons why
we exist as a profession is thatwhen you have 2300 LB people
(25:32):
running into each other, eventually an injury's going to
happen. For.
Sure. And and you know, there are
certainly the freak injuries that that happened.
There's somebody sitting on the bench and gets hit by a foul
ball in the head and suffers a concussion that you know, bad
(25:56):
things unfortunately do happen and we could not prevent every
injury. Definitely not.
For sure now. Now when I look at my injury
stats, all I'm going to see is astat stat sheet of bad luck.
That's the first thing that's going to pop in my head now.
(26:16):
Oh yeah, the whole concept of being injury prone, yes, there.
Yeah. I can't remember it right now,
but somebody did a a really nicearticle, that research article
that does show that some people just genetically are at an
increased risk of injury. Wow, that is really fascinating.
(26:42):
Yeah. When we genetic cell is a really
big influence, especially we were with ACL injuries.
I was just thinking that this was an internal study that was,
(27:04):
we didn't publish it, but we, weme went through, I probably had
almost 20 years of data at this point.
And I went through and I identified every set of
biological brothers that played in the NBA.
(27:29):
And in every case, if one one ofthe siblings tore an ACL, the
other one did. Wow.
Wow, that's. Interesting.
And if one or if one sibling didnot rupture an ACL, the other
one didn't. So now that that only includes
(27:50):
at the professional level, we didn't, I didn't go back and
look at high school or college, but it was still really an
intriguing fact. And I'll ask why students in the
classroom, how many people here have ruptured an ACL?
(28:11):
Depending on how active the class hands will go up.
And then I'll say, OK, of those that did, who have we who have
you have had a sibling rupture in ACL and not everybody's hands
stays up, but it's like, Oh yeah.
(28:35):
That's interesting. I, I feel like it was, I feel
like this was a quite a few years ago now, but like, I think
it was like a session at NATA orsomething.
They were talking about certain genes and like like a certain up
regulation, down regulation of genes kind of led to or kind of
hinted at possibly being an increased risk of ACL tear.
(28:56):
So yeah, I have heard of that for sure.
Well, just recently one of my athletes tore their ACL and I
said, hey, you know, it was, I believe it was their right leg.
So I was like, well, you're not going to be able to drive.
So I was like, hey, do you have like, can you call your parent
to pick you up? And they're like actually my
parents on on the way to take mybrother to ACL surgery right
(29:18):
now. He.
Boils down, it boils. Down to you get to say thanks
mom and dad. I was like, you guys get to do
rehab together, Yeah. The brothers at rehab together
stay together. So we've kind of hinted at this
(29:42):
again, just kind of like the class that you do teach on this
and you know, we've, we've been like very lucky to actually take
this class, but kind of where can someone kind of learn more
about epidemiology if they're not able to like take a class?
What I would recommend is getting on the Google OR and not
(30:03):
to discriminate if you're a Bingperson, and search Zack Kerr.
Kerr, who is at University of North Carolina Chapel Hill.
He's not an athletic trainer, but he is without a doubt the
(30:28):
most active sports epidemiologist out there.
Now he is is provided so much information to the athletic
training profession regarding sports epidemiology.
He he works with Dataless, who does the the NCAA and the high
(30:50):
school study, does all their statistical analysis.
You know, it's really cool to see this all come together
because as we've talked about before there as an athletic
trainer and in our profession, we do collect so much data.
But it's really what do we do with that rather than it just
(31:13):
sitting in a computer or software somewhere.
How can we actually utilize thatto show our value to help
decrease injury risk to etcetera, etcetera?
And again, this is probably a workload issue.
Mm Hmm. But athletic trainers aren't
(31:35):
always the best at maintaining good records.
And I think that if you take an athletic trainer that works in
the private for profit setting versus you all, there's more.
(31:58):
There's suddenly the demand, theexpectation that those
clinically, these people document everything that they
do, be it the diagnostics or intervention.
But that shows the, the word that shows what, what people are
(32:21):
getting out of it. We, we don't do quite as good of
a job in the quote UN quote traditional setting this we
should. And you know, anytime you
generalize like that, you're generally wrong.
But I I think to the it's an area that I think everybody can
(32:47):
improve it. For sure, yeah.
And you know, that's what I kindof tell my students like when
I'm kind of teaching them the concepts of, of epidemiology and
kind of calculating injury rate is just this like we as athletic
trainers are exposed to so many opportunities to collect data.
(33:07):
And if you're, if you're documenting like your EMR has
like just a ton of data, that isdefinitely usable if you have
the time to do so. And some you have to pull out
manually and some of them depending on what EMR you use
like you can create those reports like you were talking
about. Definitely depends on your
(33:29):
question. AI can be used for good or evil.
I'm working on the evil part, but I I can see in the very near
future you tell your computer Sandra Harris, right?
(33:53):
ACL rupture, blah, blah blah. It'll sort all that.
Put it into the Mr. for you and then a using our data, calculate
the rate of ACL injuries, OK, now calculate that rate male
versus female or football versusbasketball.
(34:15):
So the, the good aspect of AI are, are those type of things
that will make the use of our time more effective.
You don't have to to sit there and and and figure it out
yourself. I was going to say, man, that
(34:37):
would cut down so much time for me.
That would be fantastic. Only if you use it for evil.
I think that kind of leads into if time's a little tight, how
can you analyze the data either with AI, without AI, if you're
(34:58):
like, do we just need to focus on the time to document or like
what advice do you have for athletic trainers who you're
right, the workload is just thatmuch Well.
First of all, we we have the legal obligation to document
(35:19):
this anyway, so. Absolutely.
That that needs to be where youryour emphasis is.
It shouldn't be that challengingtime wise to again if your EMR
is set up for it or you downloaded into Excel to go
(35:41):
through it and and make those calculations for.
Sure. Now some of these the numbers
become a little bit unstable if your N is less than 30.
So are we really limited by thator how do you recommend if you
(36:02):
have like a smaller? That the the the low N is is
most usually effects confidence intervals, so if you have
something with the low end you could use the odds ratio for
relative risk calculations. Nice.
(36:28):
You ready for an action? Yes, I think it's time for this
is Sandra's favorite part because she's all about action
and what can we do right now. So what can an AT do today that
can change their practice? And athletic trainers listening
on their way to work right now, they're going to go into their
into their office and they're going to change something today.
But first of all, I hope they have a nice day.
(36:52):
Keep things in perspective. The one thing we you've heard,
the expression garbage in, garbage out.
The more accurate what you document, both in terms of
detail and being sure that you capture everything, gives you
(37:13):
that foundation of data that youcould use to withdraw later on
for. Sure, I like that.
That's what, again, that's what I try to tell my students.
Like whatever you're getting outof your like EMR or whatever
data you're trying to look up is, is only as good as what's
being put in. So you know, that should kind of
(37:36):
be like your kind of expectationof like if you've put in a lot
into your EMR and a lot into that kind of data usage, like
you should be able to get a lot out of it.
Or if you only put kind of limited like you, it might kind
of limit what you're able to actually pull out of it.
And it was the other thing we spoke about is OK, if when you
(38:00):
identify the body part, if you go leg, that's by the end of the
season, you're going to have a whole lot of leg.
As a matter of fact, I bet you you have twice as many legs as
you have people. And then if you go leg, knee,
you're going to take the end from here down to here and then
(38:23):
you go knee. We'll, we'll, we'll show the PCL
some love here, the PCL. So what you say, if you drill
down too deep it, you're not going to get that end to make
the the really rational conclusion from it.
(38:48):
A lot of this is just the eyeball test too.
If your your your men's team hasone ACL rupture over the last
five years and your women's teamhas 22, you you, you don't need
to take a class to figure out that's not right.
(39:09):
Yeah, yeah, that, you know, that's.
A good way to say in southeast eastern Ohio, that ain't right.
That's a good way of putting it for sure.
There are times you could kind of just look at it and just be
like something weird's going on,yeah.
And then you can take that something weird and build it
into a more scientific hypothesis for sure, but it
(39:36):
takes the weirdo factor to kind of trigger that.
Yeah, that's true. And look at that.
Science started by weird. Weird science.
Yeah, see there. You go.
Finally, a movie reference somebody gets.
(39:58):
Honestly, also talking about just streamlining, 'cause you
kind of brought it, brought it up.
If you just put something in thenotes of your EMR, right, it's
going to be a lot more difficultto pull out later.
But if you use like your drop down features or we created a
sign in on an iPad that goes directly to an Excel file.
(40:18):
So then we can take that data and do whatever we want with
that and we can. Sort of by sport or whatever I
can use that to then put into myEMR.
So really if you, if you find a system that works for you and
you're streamlining, it's going to be a lot easier than looking
in like every SOAP note you've written, like clicking the
person's name, clicking open, clicking notes, clicking the and
(40:41):
then and then reading through and trying to find some piece of
data. If you streamline, streamline
the process, it's going to be a lot easier on you on the back
end to find the time to do all these things.
Yes. A1 day AI.
Yeah. And again, that would be in a
perfect example. OK, take these SOAP notes,
(41:05):
identify the body parts, identify the intervention.
Nice. Our university has some pretty
harsh policies on use of AII. Encourage our students to to use
it. I think that's one thing that
(41:26):
I've kind of noticed is I think I feel like people should at
least get comfortable using it as a tool to kind of help, you
know? And I told tell them when I was
a kid, there was a device that was invented that was going to
destroy humanity as we knew it. That was called the calculator.
(41:51):
People are going to have calculators and they're not
going to know how to do math. Well, no.
Having the calculator just makesthe application of math easier.
You don't have to remember your multiplication tables.
The calculator obviously does that for you.
(42:13):
Then the the teacher would say, yeah, but you're not always
going to have a calculator. Let me see if she's still alive
yet or not. I do remember that argument all
the time. I think math is now much more
usable by more people and it's going to be the same thing with
(42:35):
AI and information. I mean, calculating all this
data without a calculator I can't even imagine.
But I, if you go to like Gemini and you say, OK, I've got 142
athletes, there were seven wristfractures, but calculate the,
(43:02):
the you know, the risk grade, etcetera for it.
It may need more data than my quick little stem there, but it
it can do it for you now. Nice, that's interesting.
That's really cool. I I didn't even think of yeah.
I'm telling you how to cheat formy class now that you're done.
Hey, we're hey, we're already took the class.
(43:23):
We're good. Is this is this not a good time
to bring up that after I did my assignment I used AI to double
check that I made the proper conclusions?
Did you really? I did.
I don't remember that. I'm completely fine with that.
I think she congratulated for that.
(43:44):
I would say it's encouraged. But you still didn't pass.
You mean AI didn't pass? Yeah, I did.
I can develop an AI program to do this and we can call it
(44:07):
ChatGPT you. Heard something?
You heard it here first. Yeah, well, I'm going to retire
from this job here and go do that.
Do I think we just we just had our we just found our first AI
infused ATHI training EMR. Alfie makes a comeback.
(44:34):
What's Alfie's last name? It must start with an I.
No for because IP systems. There we go.
Yeah, IP stood for idiot proof. That's pretty funny.
I like that. Sweet.
(44:55):
So just to wrap things up there,we just talked about some data
that we've turned into value. Like I think in the episode we
we talked about like the sign insheets.
But also, for example, somethingthat I use is my injury report.
So like every day I create an injury report for or every,
(45:16):
every practice day, I should say, I create an injury report
for football. And at the end of the season,
the last two seasons, I've been able to take those because it's
already in an Excel document andI just put them in a new Excel.
And then I'm able to really filter out things and, and
figure out what injuries, what sides of injuries, the positions
(45:41):
and, and just really like whatever I put into it.
Like we've said, an episode is really what you get out of it.
Yeah, for sure. I think that again, that's like
I said during the the interview is that's one of the most
important things that I teach the athletic training students
is like the data you get is onlyas good as like what you put in,
right. So if you're trying to ask a
(46:02):
specific question, right, you got to make sure you have the
data to kind of help you. Or if you're just thought of
that question and you haven't collected that data, now you
know where to start and like, oh, well, here's what I'm
thinking. Here's how I should collect that
data. Yeah, exactly.
So it's a lot more accessible than I think people think, for
sure. It just takes a minute to get
started. And then once, once you really
(46:22):
get started, then you're going to be like, oh, I could look
into this. I could look into this, I could
look into this. Just opens a Pandora box of
data. For real, so if you guys are new
here, we do every episode as either interviews like this one.
We do other episodes as stories from real life athletic trainers
about various topics all around the world, athletic trainers
(46:45):
from all around the world, whichis really exciting.
And then we also do education episodes, which Randy heads and
those ones are worth category ACus.
Thank you so much to athletic training chat and clinically
pressed. If you're interested in looking
at those C us, we actually have a sale running.
We have some free ones, but we also have a sale running through
(47:05):
the end of national Athletic training month.
So you can use code NATM 25 for 25% off those.
C us. There's also still a couple more
days of NATM. So because of that, we are still
running our giveaway if you're listening to this as it comes
out. So enter our giveaway with Medco
to win a Merritt Mueller kit andsome podcast merch.
(47:27):
Super exciting. And then if you're interested in
more Cus, you can also use code 80 corner for $101.00 off
Medbridge. It is a reporting year.
Yes, it is. So if you guys are interested in
sending your stories or just chatting with us, head over to
our Instagram at 80 Corner podcast where you can do a bunch
(47:49):
of the things that I already talked about.
We also have a bunch more links and stuff down below in the
podcast description. So I think that's all my fine
print. Thank you for helping us
showcase athletic training behind the tape.
Bye.
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