10 Clinical & Financial Industry Benchmarks to Know from the State of the Industry Report
Here’s what to expect on this week’s episode. 🎙️
Have you ever wondered what other surgery centers are experiencing for:
• Average Block Time Utilization
• Insurance Pre-Auth & Verification Rates
• Case Cancellation Rate
• Patient Deposit Collection Rate
• Average OR Duration & Recovery Time by Specialty
• Days to Bill by ORs
• % of Claims Denied
• Average of Days Not Worked by Age of Receivables
• Average Net Revenue Per Case
• YoY Net Revenue Growth
If the answer is yes, now is your opportunity to get a window into how 450 surgery centers are performing and how you compare!
We are in an era where data-driven operations are the only option, and using data to inform your work and being surgically precise in how you operate is critical to thrive. Surgery centers that embrace this shift will be the ones to remain on top. That is why we wanted to take the time to dissect the top 10 key metrics that came out of our most recent State of the Industry report – to help you embrace this mindset and get started.
Thank you to Will Evans, HST’s Senior Director, Data Science and Insights, for joining us for this discussion.
Find the full episode on Apple Podcasts, Spotify, or YouTube to hear all the details.
Episode Transcript
0:01
welcome to this week in surgery centers if you’re in the ASC industry then you’re in the right place every week
0:08
we’ll start the episode off by sharing an interesting conversation we had with our featured guest and then we’ll close
0:13
the episode by recapping the latest news impacting surgery centers we’re excited to share with you what we have so let’s
0:20
get started and see what the industry’s been up [Music]
0:26
to hi everyone here’s what you can expect on today’s episode last week we
0:32
held a live online event with Will Evans will is the senior director of data
0:37
science and insights here at HSC Pathways and we spent an hour reviewing 10 of the most compelling clinical and
0:45
financial industry benchmarks from hst’s latest state of the industry report so
0:50
if you haven’t seen it we’ve released a state- of the industry report in late September and it includes best practices
0:57
keepy process steps over 125 kpi ideas and benchmarking data for every step of
1:03
the patient journey and for nearly every recurring administrative Duty as well we
1:09
are in an era where datadriven operations are really the only option and using data to inform your work and
1:17
being surgically precise in how you operate is critical to thrive and
1:22
surgery centers that embrace the shift will be the ones who remain on top so that is really why we wanted to take the
1:29
time to not only create the report but also dissect the top 10 key metrics that
1:34
came out of the report and help you Embrace this mindset and get started so if you have ever wondered what other
1:41
surgery centers are experiencing for average block time utilization case cancellation rates patient deposit
1:48
collection rates average net revenue per case now is your opportunity to get a
1:53
window into how you’re tracking and Performing hope everyone enjoys the episode and here’s what’s going on on
2:00
this week in surgery centers hi everybody thanks so much for
2:08
joining us this afternoon I’m Erica Palmer with HSC Pathways and I’ll be moderating the webinar today if you’ve
2:15
been to any of our webinars before you know my usual shiel but this webinar is
2:21
truly for you so we do want it to be as interactive as possible so please use
2:27
the Q&A box that any time if anything comes up and I’ll make sure that either will or I can address the question that
2:33
you have don’t be shy we want to get all of your questions especially with the data that we’re showing it is unique to
2:40
HS and we want it to be a discussion you know if you’re seeing different metrics at your surgery center let’s talk about
2:48
it all right so what are we going to do today we are in the middle of our our welcome and housekeeping items right now
2:56
I want to take a moment to introduce the report to you as as well um obviously
3:01
today we’re focusing on 10 industry benchmarks but those benchmarks did come from a report that we published uh last
3:08
month and then talk a little bit about why this stuff matters and then I promise we will spend the bulk 90% of
3:14
this hour um talking about those 10 key
3:20
metrics so I’ve already introduced myself um I’m on the marketing side at HST and then I’m super excited to have
3:27
will Evans with us today he is our senior director of data science and insights and we uh would not have been
3:35
able to produce a report like this or get into kind of the nitty-gritty of some of these data points without Will’s
3:42
guidance so really excited to have him with us
3:49
today um okay so if you’re not familiar with the report I’m going to put it in the chat um whenever I have a second and
3:55
then I will it’ll be a next week’s email um you’ll be redirected to the report when this webinar ends so I’ll make sure
4:02
that you have access to the report itself um but what we decided to do was
4:07
publish a report focusing on best practices and proven data for optimizing
4:13
ASC operations uh so it’s a pretty extensive report there’s over 45
4:19
chapters with a ton of different data points and most importantly a lot of kpis so we’re always you know
4:26
encouraging surgery centers and clients to focus on data and in with doing this
4:31
report we’re trying to give you some examples of how to get started um or if you already been doing it for years and
4:37
data is a core piece of what you’re doing um I would love your thoughts on the kpis that we shared um if you think
4:43
we missed any or you know just general feedback of really trying to get everybody started on the kind of the
4:50
data front here and the report itself has six key chapters we really tried to
4:56
look at the entire patient Journey from the moment the doctor and the patient decide yes we’re moving forward with
5:02
surgery you know all the way down to the moment where they are being discharged from your facility so we’re looking at
5:09
pre-day of service day of service and post and then we’re looking at the regularly recurring operations so what
5:15
should you be doing on a daily and weekly basis what should you be doing on a monthly quarterly basis and then an
5:21
annual basis as well so again I will send this report um but the 10 data
5:27
pieces that we’ll be uh looking at today all came from this report and there’s even more in
5:35
there okay so why why are we here why does this
5:40
data matter you know kind of where is the surgery center going so what we’re seeing across asc’s is that the world
5:49
has really changed from what it used to be it used to be a lot easier to manage things in an ASC um but you know things
5:56
are getting more and more challenging uh reimbursements are stagnant or even lowering uh in some cases competition is
6:05
increasing across the board more hospitals are getting involved and taking interest in outpatient spaces
6:10
than ever before there’s an increase in higher Acuity cases I don’t need to talk
6:16
to any of you about the staffing issues that are going on but unfortunately it doesn’t seem like there’s any end in
6:22
sight based on projected models so you know Staffing shortages how are we going to overcome that and then of course I’m
6:29
sure you’re experiencing just like Rising costs of everything across the board especially supplies you know the
6:35
economy is really taking a hit especially for asc’s so Precision is really the only
6:44
option here and the new game in town so when we’re talking to those um who are
6:50
most successful and the most profitable centers they’re really focused entirely on efficient
6:57
datadriven Precision operations so just like all of you you know are so
7:03
surgically precise in the operating room we need to take that mindset and move it to the business side of the house and
7:09
shift from imprecision to Precision operations and you know we’d be
7:16
Hypocrites if we didn’t prove this with data so we’re seeing that there’s actually a huge difference between those
7:22
that that take this mindset and those that don’t some are really succeeding and others are struggling to you know
7:29
not forget Thrive and grow but just stay in business so two metrics that we’re
7:34
really seeing a difference here on is iida so basically like earnings or profit margins for businesses and then
7:40
of course block time utilization which we’ll spend some time on today as well and when you really compare the average
7:47
to those who are in the top cortile or you know top 10% there’s a huge
7:53
difference and it might only look like 10 or 20% across both of these metrics
7:59
here but that could equate to hundreds of thousands or or millions of dollars of extra earnings which of course could go
8:06
towards all the issues we’ve already talked about Staffing supplies recruitment whatever your facility needs
8:12
and the difference can be really Stark and just reminder because I’m I know I’m moving quick you’re going to
8:18
get the slides you’re going to get the recording so you can spend more time with these numbers as
8:24
well so what are top performers doing that is performers doing that is setting
8:29
them apart there’s really six primary things here so being surgical with o
8:35
utilization and profitability you know looking at the numbers regularly that all we were just talking about and
8:40
trying to improve them you know doing things like physician Recruitment and having Physicians come inbound rather
8:47
than you having to spend so much time and effort trying to recruit outside Physicians they’re automating manual
8:53
processes we are trying to remove as much human intervention in manual labor and make things as simple and
9:00
straightforward and automated for you um of course evaluating individual
9:05
case profitability so that at the end of the month there’s no surprises there’s no Panic about what cases you took on
9:12
that ended up not being profitable you know at least you’ll have the opportunity to to say yes or no when a
9:19
case comes across your desk monitoring case mix and Acuity and then of course
9:24
for forecasting hiring needs and Supply needs
9:29
and this kind of thinking and this this strategic approach can really change
9:35
everything for every stakeholder that touches your surgery center so for your admins or the business office folks it
9:42
moves them from a good amount of reactive work or redundant low value tasks uh to being able to Pro be
9:48
proactive and work on higher value things uh for your clinical team it moves them away from doing clerical work
9:55
and gets them back to what they love which is working with patients and actually being able to use their degrees
10:01
to their full potential and skill set Physicians of course you know on the business side they don’t have to worry
10:08
about all the nuances and they can instead think about their patients and the business as a whole if you have
10:14
management groups involved you know it helps them go from delayed insights to benchmarking across the whole portfolio
10:20
and trying to identify patterns and then of course Financial outcomes oh the
10:28
goal but if it was as easy as all of that everybody would be in the top
10:33
cortile so we fully recognize that this is an extremely challenging place to get
10:38
to and if you’re lacking automation you’re missing data you’re having all
10:44
these Staffing challenges and you have limited time it’s going to be really difficult to get to this place so in the
10:51
data that we’re presenting to you today and kind of this mindset we would love you all to shift into it can really help
10:58
over overcome some of these biggest hurdles and then of course you know HST was purpose built to help you do exactly
11:05
that we really do strive to make data uh live at the core of everything we do and help you run Precision operations and I
11:13
hope that um by the end of this webinar with the data we’re sharing with you and the time we’ve put into this that really
11:19
comes across all right so enough of me for a
11:24
second let’s do a quick poll first question we’re going to do two polls today this is our first one what other
11:32
sources do you use for industry benchmarking I would love to know um
11:37
where else you’re finding your data and you know kind of what you find most valuable so I will give everybody about
11:45
30 seconds to complete this poll and then I will share all the results as well and while you’re filling out your
11:52
answers I did just put a link to the full report in the chat as well okay so I’m ending the poll sharing
12:01
the results hopefully you can all see this but um ASA great resource ASU
12:07
quality collaboration is another great resource I think it’s potentially underutilized they have a lot of great
12:13
clinical metrics um available awesome all right thank you
12:19
all so much for sharing all right so to the good stuff first metric we’ll be
12:25
talking about today is average block time utilization so will I’m going to hand things over to you for a second can
12:31
you help us understand how this data point was collected uh sure Erica so for this
12:38
metric in particular there’s kind of two pieces that you need to put together to be able to calculate it and so the way
12:44
that we went about this and fully admitting that there are multiple ways that you can look at not just block time
12:50
utilization but o utilization in general the way that we calculated this here is that we identified scheduled blocks
12:57
within HST and then we tied cases to that reserved block based on the
13:02
physician or group that scheduled the case so if a physician who is not part
13:08
of who is not the physician that reserved that block and is also not a part of the group that reserved that
13:14
block if they perform a case during that scheduled block time in that o we
13:20
actually end up considering that non-block time and so we didn’t count that towards this metric so this
13:25
specific metric is really just calculated by dividing the um associated with performing cases um
13:33
by The Physician or The Physician Group that scheduled the the original O
13:39
block and this is one I think like going forward in the future there’s multiple ways that we’ll look at it because we
13:45
we’ll look at block Time and non-block Time versus the scheduled block and then we’ll look at overall o utilization as
13:52
well and really we would want to understand how do all those three kind of metrics work together to give you a
13:59
holistic view of O utilization and block time
14:04
utilization perfect thank you yeah I think this was one metric that we’ve actually gotten a lot of feedback on so
14:11
far just because of the way we calculated it and and to your point the way others calculate it it can make a
14:17
huge difference in the number that we come to but I’d like to think if we were all sitting in a room together you would
14:23
all be nodding along at the sentiment that you know a surgeon might have every
14:28
Monday from 9: to 12 blocked for them and then most 42% of the time it ends up
14:34
sitting under unused which can be frustrating but it also is just a huge
14:40
missed opportunity for Revenue generation and we’ll reference this metric again when we actually get to um
14:47
our final metric which would be year-over-year growth but this could be a huge opportunity to generate more
14:54
revenue for the organization and you know some I put some tips in here to improve it I’m sure you all have a lot
15:01
more you could share but you know being able to share your o availability online
15:07
with office schedulers setting internal goals for Physicians and staff and just
15:12
educating on the importance of high utilization I think could be really
15:17
great ideas to get to increase this or lower the number of but when your o is
15:23
not being utilized and you know It’s tricky because of course it’s all in the
15:29
surgeon’s hands right if this is their block time trying to educate them and have a conversation with them as to like
15:34
you know at what point can maybe we let it go and try to get other surgeries in there whatever initiatives work but
15:40
improving this number is just a a critical component to increasing your
15:47
bottom line before we move on there’s two other notes I I do want to call out
15:53
about this one when you start breaking this apart by specialty you do see a
15:58
different variations in O utilization by specialty like we have some gastro focused ORS and asc’s where you see this
16:06
number really high where they’re up around 80 or 90% there’s also like pretty big
16:12
dispersion amongst that same the the the the gastro groups but if you drill in by
16:18
specialty you’ll see different variations and distributions of this metric and then uh the other thing is
16:25
this one in particular is a great lever as Erica mentioned uh later on we’ll talk a little bit more about it but for
16:31
identifying additional opportunities if there’s unused block time and you can publish that or you can release that to
16:36
other for other availabilities uh it just helps you understand more of your Precision
16:42
operations perfect I do have three questions for you so how do you and also
16:48
I should say for the sake of time we might have to skip some questions but we will absolutely save all of these and
16:54
reply to all via email uh if we can’t get to them live but how do you track utilization for
17:00
unassigned Block times we have an issue with that sometimes we have doctors that post a lot without assigned block time
17:07
we have a hard time figuring out how to capture that right now that ends up falling
17:12
under the the non-block time and so when we do the math on this one we basically
17:18
have a flag where you can include or exclude that and I’ll be honest I don’t think we have a great way of of doing it
17:25
yet that’s this is where we start to morph to thinking about overall o utilization but that’s definitely one
17:32
that I think as we go through this again uh for 2024 and we start to calculate some of these metrics that’s more of
17:38
kind of the Fidelity that we would we want to uh start to tease out definitely is block calculated by MD
17:47
scheduled time or actual patient in room time so the block is scheduled by based
17:55
on what the what the doctor is scheduling for for actual consumption of
18:00
that time there’s a hierarchy within hsd that you can go through where there’s at
18:07
at certain facilities do it in different ways and um I think if you have eart you can literally get the entrance and exit
18:13
times for the O but basically we step through a process of what’s the highest
18:19
level of granularity is it an echart based in andout time all the way down to what was just the schedule start and end
18:25
times for that case and we go through and we look at what gives us the best indicator and what we think is the
18:31
highest Fidelity data point to use thank you and last question I’m
18:37
hoping you know the answer because I do not how do you adjust for Physicians that have flip
18:45
rooms I don’t have a great answer for that one okay Kelly I’m saving this and
18:50
we will get back to you okay so let’s keep it moving to
18:56
metric number two so here we’re looking at insurance preo and verification rates
19:02
so will can you give us a little insight into this metric please sure I’ll start
19:07
with insurance verification that one’s a pretty straightforward metric here within HST we just went through and we
19:14
summed up or we counted all the cases where they had the insurance verification complete and so it’s a
19:20
simple just yes or no and we divide that into the the total count of cases that
19:26
had insurance or that either did or didn’t have insurance verification insurance pre-authorization it’s a
19:32
basically a similar methodology but for counting the yeses here uh we um include
19:38
multiple statuses there are some that don’t require a a pre-authorization to
19:44
be completed and so we have to control for that but uh the shortest way I think to describe this is where insurance
19:52
pre-authorization was not completed that’s anywhere where it’s a no or it’s a null value in the hsd system and so
19:58
it’s the same methodology you just sum up the yeses divided by the total base thank you first question how do you
20:07
know which procedures do not require
20:13
preo I actually don’t know that’s a good question that’s one to be honest in the
20:19
HST system the code that we use is NR and that’s where it’s not required but I
20:25
would have to talk to one of our internal product experts to to give you a good answer on that one sure and so
20:31
Emily we can definitely give you a little bit more insight there good question though and I think you know
20:37
with both of these metrics it’s it goes without saying that they directly impact your reimbursement and revenue
20:43
collection and ultimately patient satisfaction physician satisfaction so
20:48
really honing in on your processes and also trying to take out as much um human
20:55
component to it as well and making sure that you have systems in place where you can continuously run Insurance
21:01
verification you know not just once but whenever you would like to so as soon as you receed the case maybe the first of
21:08
the month you’re running Insurance verifications for all the cases in the upcoming month and then on the morning
21:14
of every day every morning you’re running Insurance verification for your procedures for that specific day and if
21:21
you don’t have an automated way to do that you’re uh going to spend a lot of manual time doing it or Miss cases where
21:28
insurance has lapped for multitude of reasons so obviously you know trying to identify trends when you are having
21:36
issues with this you know are there certain procedures payers are there time periods you know that you’re experiencing issu most issues with this
21:43
when um deductibles reset on January 1 or whatever it might be you know fixing
21:48
communication between the front office and the billing staff utilizing technology um adjusting documentation
21:55
practices and ultimately training staff too I think for me that’s just a big takeaway from all of this if you’d
22:03
haven’t had the opportunity whether it’s during a staff meeting or whatever it might be to really educate everybody
22:09
within the in the ASC walls as to the importance of all these metrics and why it matters I think that’s also just a
22:16
key like education is just a key piece of this too all right metric number three case
22:25
cancellation rate so we talk about this all the time we got lot of questions about this I actually saw a thread in
22:30
the askap form recently where someone else was looking to Benchmark you know see if where they were at compared to
22:36
their peers will can you tell us a little bit about case cancellation rate please there this is another one that
22:44
was it’s a pretty straightforward calculation where we’re just counting up the number of cases that were scheduled
22:51
in q1 and Q2 of 2023 but then were canceled and dividing that by just the
22:57
total number that were scheduled let me see if there’s if we had any caveats in here no I think it’s a pretty
23:03
straightforward calculation on this one yeah I agree and I I think this obviously it’s an easy one for people to
23:10
understand and an easy one for everyone to understand the impacts so you know obviously it impacts your bottom line
23:16
it’s frustrating for staff physician um and staff satisfaction but also patients
23:21
you know unless they’re the one doing the cancellation but you know this is another place where you can really
23:27
improve your by identifying the trends so is it patient related is it an equipment issue
23:33
is it just an unforeseen emergency what is it and then you know again T is it
23:39
around the holidays when are you experiencing your highest case cancellation rates year over-year so
23:45
that you can uh prepare for it you know automating patient text reminders and preop instructions so you never have to
23:51
cancel a case because the patient didn’t know they didn’t have to eat whatever it might be offering Financial counseling
23:57
so is a patient get arriving the day of and they’re seeing their bill and they haven’t seen it yet and they’re stressed
24:03
and they’re deciding you know they’re going to walk right out or whatever it might be obviously if you’re having
24:08
equipment issues you can hold more frequent equipment and supplies checks so first identify those Trends and then
24:14
you can really go from there all right patient deposit
24:22
collection rate this is a fun one will how did we get here
24:28
uh sure so this one uh within HST there’s two fields that we use to calculate this there’s the um it’s the
24:36
expected patient deposit amount and then there’s the actual patient uh deposit
24:41
collected um and so the math here is pretty straightforward um we’re just dividing the actual amount the actual
24:49
patient amount collected by the expected amount collected which on the surface is pretty easy to do for whole and an
24:56
aggregate but we know that the this isn’t used by all centers and so when we calculated this 53% number we had to go
25:03
through and um basically scrub out some of the data that um we knew wasn’t accurate and so generally speaking how
25:10
we did that was we looked for uh centers that just weren’t populating the
25:15
expected collection data and in some cases they were only populating it maybe very sparsely so to basically try to get
25:23
to a high fidelity number we would remove the the centers that aren’t using it or are basically not using it
25:29
reliably so that we could try to triangulate a number that we felt pretty good
25:34
about perfect thank you yeah I would love to hear in the the Q&A box too if
25:40
you know any of your numbers off the top of your head for any of the metrics that we’re sharing and you’re comfortable putting them in the Q&A I’d love to hear
25:47
them because this number 53% collection rate on expected patient deposits it
25:54
just seems so low and I’m sure everybody would want it to to be higher we do have one question will are you assuming the
26:01
center has the correct expected payment this number changes when EOB
26:07
arrives uh yes essentially what we’re doing is we’re trusting them to put in the
26:13
correct amount fully knowing that yeah this isn’t it’s never going to be 100% I think objectively accurate data and so
26:21
that’s why we’re kind of declaring the metric these are the basically the parameters that we’re using for it over
26:27
time I think this is some one that we can probably evolve and maybe change and
26:32
look at it different ways but yes perfect thank you yeah and I know
26:38
you know we talk about price transparency all the time here but a
26:44
very easy way or a very straightforward way I should say to increase this number is to send an accurate patient estimate
26:53
to the patient as far in advance as possible have it automated know nobody on your side should be manually
26:59
crunching numbers in order to tell a patient what they owe and they certainly should not be finding out what they owe
27:05
for the first time when they walk in the day of surgery so not only you know automate the process of generating the
27:12
estimate send it to the patient via text or email so that it’s you know no one can ever say to you I never receive this
27:20
and then also offer them a way to pay online have an immediate call to action
27:25
and offer them credit card payment online payment whatever it might be um we actually did have someone share
27:33
so Diane shared uh we use this as a quality study which is um a great idea
27:38
and we have went from 36 46 36 to 46% to sustaining in the
27:45
high 90th percentile so that’s extremely impressive if you would like to share
27:51
what you did to get to that number I’d love to hear it I’m sure everyone else would that’s awesome Diane thank you for
27:57
sharing that that so you know a couple ideas increase collections by automating
28:02
that cost estimation process internally and then of course just offering transparency at every level you know of
28:08
course you can do everything that you can patients are human so there’s that element to it but by
28:15
offering an easy way to pay in advance you’re just setting yourself up for
28:21
Success there this is this is another metric where when you step into it and
28:26
you look at the distribution of outcomes um you do see centers as kind of Diane
28:32
mentioned where they’re meeting 90% but like solidly into the 80s and
28:39
90% they’re collecting a really high rate on their expected deposits across
28:44
millions of dollars there it’s not just there’s a weird outlier where the center doesn’t do a high volume but they do a
28:50
great job of collecting on their deposits there are ones that are there are centers that are legitimately
28:56
outstanding at this that’s awesome something to strive
29:02
for okay so let’s talk about average o
29:07
duration and recovery time will can you share how we got to these numbers please I know they’re small again we’ll send
29:13
them out but sure sure so this one the math for kind of O duration and Recovery
29:20
duration is pretty straight forward it’s really just what’s the entry and exit times for the o or the procedure rooms
29:27
uh same thing for Recovery rooms and so it’s really just identifying what’s the
29:33
best metric what’s your highest Fidelity entrance and exit time and then subtracting that and averaging it out
29:39
the other piece for these is how do we map to how do we map the basically all the cases to Specialties and the
29:45
methodology we chose is to basically use the primary CPT code associated with a case and basically map that to to a
29:53
specialty and that requires some level of normalization within h not everyone codes all their Specialties
30:00
the same way or they don’t use the same abbreviation and so just you know when you think about it some Specialties like
30:06
ENT some of them are labeled as ENT with a three-letter abbreviation whereas others are they use Otto like
30:13
oenology and so we had to do some cleanup and kind of coding of the data on the back end to to map all the cases
30:20
to Specialties yeah Will’s being humble he really took one for the team here and
30:26
categorized all of our CDT so we can get to this nice clean graph here so yeah I
30:31
think this is it’s just really interesting to see and again you know within your own Surgery Center kind of
30:37
where you’re trending are o times and Recovery times increasing decreasing why
30:43
uh why is it happening because obviously the time you spent in the O and the recovery area directly influences
30:50
operational cost so by kind of understanding and optimizing the time in
30:55
the O and in the recovery every time uh you can obviously improve your bottom line but it also enhances the patient
31:03
experience increases satisfaction across the board and on the recovery time side
31:09
you know you’re really showing that you’re prioritizing the well-being of the patient which will lead to positive
31:14
clinical outcomes and of course Pat patient
31:22
satisfaction all right days to Bill bys
31:27
what do we have here will sure so this one um again there’s kind of two pieces
31:33
to how we um calculate this metric the first one uh days to Bill that’s a
31:38
pretty straightforward it’s uh really subtracting um the date the first bill was sent um from the the admit date or
31:47
the date of service and then you can average that over any number of basically groupings but the other piece
31:53
is how do we identify the number of ORS for an ASC and for that essentially what we did was we went and we counted the
32:01
number of unique o and procedure room names by facility and then using that we
32:08
were able to identify how many procedure and O rooms a facility had and we basically Bend those into different
32:14
groupings that you see on the bottom of the chart perfect thank you and I know this
32:19
was one we had gone back and forth on just because there’s so many ways to kind of slice and dice and look at this
32:25
data um but obviously number of ORS is kind of an equalizer that everybody can
32:30
look at and and relate to so obviously days to bill is just a key indicator of
32:36
the efficiency of your entire revenue cycle you know timely billing contributes to timely reimbursement and
32:43
it directly affects the speed at which your surgery center can receive payment so obviously the lower you can get your
32:49
days to bill the better optimize cash flow reduce the risk of delayed payments
32:54
there’s really there’s really so much here and I think by kind of refining the billing process if you’re not at a place
33:00
where you want to be or if you think you’re if you’re falling short in comparison to your peers here and you
33:05
want to maintain a healthy financial position obviously there’s a lot of things you can do to improve this but I
33:11
think you know investing there’s so many RCM companies investing in different Technology Solutions training your staff
33:17
improving communication between departments there’s a lot of different ways you can get this number down if
33:22
it’s too high and you know it’s taking too long to get the the claims out the
33:30
door we don’t have any questions let’s do claims denied what
33:37
what do you have here will uh this one’s pretty straightforward calculation here we
33:43
really just count up what are the number of claims that have a denial date or a denial reason and uh dividing that by
33:50
the total number of claims that we had processed during the q1 and Q2 of 2023 um this one this is one of my
33:58
favorite kind of metrics to calculate not just because it’s specifically telling in itself but very early on in
34:05
my career at hsd this was one of the first kind of correlations we found between authorization rate and claim
34:11
denial rates and that we saw as authorization rates increased claim denial rates tended to decrease and it
34:17
was just a it was a cool study in in kind of Predictive Analytics around understanding what are the
34:24
drivers of claim denials and uh being able to trace that back to things that happened kind of on the front end of the
34:30
revenue cycle and understanding just the interplay between different pieces yeah I think that’s great and
34:37
again if anyone has any if you know off the top of the head top of your head where you’re at in terms of claims claim
34:43
denials I’d love to see that in the Q&A just out of curiosity but you know this
34:50
obviously impacts the revenue cycle so much you know they a claim denial can
34:56
easily result in delayed or lost Revenue which obviously can affect your overall Financial stability it also can really
35:02
strain the relationship between your surgery center and payers so again if you’re trying to find the root cause and
35:10
and it’s you know you’re seeing a trend with a certain payer kind of building that relationship with them and asking
35:16
them and and you know having that conversation with them of like hey every time we submit this
35:21
one claim with these same variables we’re getting denied like what are we doing wrong how can we fix it really
35:27
opening up that dialogue can help as well and again you know when you do notice if you do notice an uptick in the
35:34
percent of claims denied it’s really time to initiate a deeper dive to understand that root cause is it a
35:40
coding issue documentation shortfall again a specific procedure that’s continually getting flagged and then
35:47
from there you can focus on staff training um software and technology so
35:53
consider using Advanced billing software that can help flag potenti potential denial triggers before you submit the
35:59
claim so you kind of have that extra level of Defense before it goes too far and that that alone can substantially
36:06
reduce denial rates of course regular Audits and then engaging with payers
36:11
would just be advice here if you do want to if you are seeing some some issues in this world so before we finish up I do
36:20
just want to send out our second and final poll I know we’re talking a lot so
36:26
would love to get get some engagement here here we go I’m launching the second
36:31
one here what is the biggest challenge you’re experiencing right now when it comes to analyzing data just give
36:39
everybody a minute and I know we have a lot of different organizations on the group or on the call so whether your
36:45
management group or an independent ASC or a consultant this all applies to you all right I’m going to end the poll and
36:53
I am sharing the results now this is always really interesting in to see so we’re looking at data quality yeah that
37:01
It’s just tough right whatever data goes in is the data you’re going to get out so trying to educate staff get everybody
37:09
on board here’s the importance of why we have to input all these metrics whatever it might be lack of expertise time
37:16
constraints data security and just not sure where to begin yeah I hope you know
37:22
with the report that we did produce if you’re not sure where to begin it can certainly look a little overwhelming
37:29
just because there are so many kpis and so many data points that are shared but
37:34
it could be helpful to at least pick one or two or three key metrics where you want to start and go for it all right
37:42
thanks everybody so next I’ve lost track I think this is seven seven sevenish but
37:49
here is average of days not worked by age of receivables so take it away will
37:55
sure so this is another metric where there’s a a couple different pieces that you we needed to calculate to create it
38:02
I think the first piece to tackle is essentially figuring out the age days and so to do that we aggregated accounts
38:09
with owed balances by their age by the age of the receivables so it’s essentially how old the receivables are
38:16
since their date of service or their admit date and once you do that you can average that over basically whatever
38:22
groupings you want and then we ident then to get to the the last date that
38:27
something was worked what we did was we looked in the HST system and we identified the last date that a
38:33
non-system generated note was put on an account and that’s not necessarily like
38:39
a clinical note or or something along those lines it’s it’s when was the last date that that account or that case was
38:44
being worked and then basically once you figure out that date you calculate the difference between today or the current
38:51
date and that last note date to identify basically when was the last time that
38:57
account was worked based on the age of that case and then you essentially just average those last work dates by the age
39:05
days and you bend the age days in 30-day
39:10
increments perfect thank you yeah this is an important one you’ve probably
39:15
noticed as we’re trending we’re getting into those recurring regular regularly recurring operations that should be
39:21
taking place on a weekly to monthly quarterly basis and this is a huge one
39:27
um because obviously the older receivable becomes the more challenging it can be to collect and you know you
39:35
can really use this data to kind of prioritize followup on older receivables
39:40
and kind of implement a systematic follow-up procedure that can hopefully reduce the number of days that an inv or
39:47
receivable becomes unworked and analyzing specific age buckets and breaking down like we have here the day
39:54
is not worked into specific time frames can help pinpoint where the most significant challenges lie and again
40:00
customize strategies for for each bucket and you know kind of goes back to
40:07
that patient deposit collection rate as well you’d like to think if you see an increase there you’re going to see a
40:13
decrease here and the more you can obviously collect up front the less
40:18
issues the you’ll have on the back end of things and of course delays can arise
40:24
simply by patients not understanding their bills so by try trying to increase the patient communication provide
40:30
Clarity on procedures costs and insurance coverages and then also trying to fix and automate some of the
40:38
procedures on your end as well in terms of Outreach can certainly help fix this
40:45
number we did get one question for the benchmarking as a whole can you share
40:50
how many asc’s were queried and is it in a specific location throughout the US
40:56
and then then is it a mix of Specialties as well sure so it the total Universe of of asc’s
41:04
that we pulled data for I think was around 450 I believe I don’t remember the specific number off the top of my head
41:11
but it’s right around that ballpark but basically it was centers that we have the rights to use data for benchmarking
41:17
purposes and calculating these sorts of metrics depending on how good the quality of data was at certain centers
41:24
we did have to filter some out and so there are certain ones like the expected the percentage of expected patient
41:30
deposits that number is going to be calculated off of a smaller base since we know some centers don’t really
41:36
populate all that data and they don’t really if we include those we’re introducing skew to that data set so for
41:42
certain metrics we did have to trim it down but kind of the overall universes right around 450 centers and it pulls
41:50
from it’s not all 50 uh States I want to say it’s 40
41:56
five but we did have coverage across we had coverage across 45 of the 50 states
42:02
some of the smaller ones we didn’t if we have centers there we didn’t have the the rights to use their data in these
42:09
calculations and then it is a mix of Specialties it’s I mean I think we see the Specialties on the uh on some of the
42:16
other slides but it’s we hit a pretty broad array of them
42:22
thanks okay there are no more questions about this one I will keep it
42:29
moving all right average net revenue per case tell us about this one will so this
42:36
one this is another one that we ma to Specialties and so for here we use the
42:41
same methodology where we identified the primary CPT code and we normalized Specialties and then mapped it over and
42:48
then for net revenue we’re looking at Contract fees and this is basically a straightforward just calculation of
42:54
averaging out the contract fees by specialty once you’ve mapped that over
43:00
one caveat I did want to make here is that I believe for pain we pain I think
43:07
is a little bit higher than average benchmarks you’ll see here and I think that’s mainly because this one ended up
43:13
having a pretty higher or a relatively higher um percentage of placement of
43:19
neuro stimulators in it and I know some centers I think that will end up getting grouped under different Specialties and
43:26
so just one caveat on this one that is one I think anomaly in that I want to
43:31
call out around how these numbers were calculated perfect that makes
43:37
sense yeah I mean this metric is key right it can really drive your entire
43:42
surgery Center’s growth strategy it really provides you know an immediate snapshot of the revenue that you’re
43:48
generating for each case a lower net revenue might indicate some operational inefficiencies um which could be due to
43:55
proed procedure times High Supply costs maybe inefficient resource utilization um so really understanding
44:03
the net revenue per case it can also leverage you can also leverage this during negotiations with uh payers and
44:11
make sure that you’re receiving appropriate reimbursement as well and
44:16
this is definitely one metric that we would really recommend incorporating into your periodic performance reviews
44:23
setting targets for improvement identifying areas that might need attention and then the big one would
44:28
just be assisting uh you in projecting your future revenues so help we make
44:34
informed financial and operational decisions which Specialties do we lean into it could really drive your growth
44:40
strategy you know I know everyone’s talking about total joints and cardiovascular right now and I know it’s
44:46
kind of hard to see but that’s number one and number two in terms of net revenue per case so this can really be a
44:53
key metric when you’re talking about 2024 and Beyond and if you want to grow if you want to sell whatever your
44:58
surgery Center’s end goals are this can be a really key metric to help you get
45:06
there all right and our final metric here will talk to us about the year
45:11
over-year net revenue growth sure so here this is another one where I think
45:16
there’s kind of two pieces there’s a couple pieces that we had to calculate to put this together the first one
45:22
number of ORS that’s it’s the same method ology we used on some of the
45:27
previous slides where we’re just counting up the number of unique operating and procedure rooms at a facility and then for year-over-year net
45:35
revenue growth essentially how we calculated that was we summed up the net revenue bu Center for q1 and Q2 of 2023
45:44
and then we divided that into the sum of net revenue per Center for or at a
45:50
center for q1 and Q2 of 2022 and we did this for Apples to Apples so basically
45:56
if we had customers that came online through the tail end of Q2 of 2022 and
46:02
they were they stayed on through 2023 for HST uh we actually omitted those
46:08
from the data set right because we’re getting a smaller denominator for uh 2022 that’s going to inflate that growth
46:15
rate for that Center and so um this is one where we did have to trim down the data set a little bit it wasn’t a ton um
46:23
but basically we’re really trying to get to an apples to app um calculation on the same cohort of
46:30
centers so that we can really understand what’s the year-over-year growth that’s happening in the ASC industry by the
46:37
size of the facility and these I would say like there are certainly ranges
46:43
around each of them like it’s but the overall trajectory is what you see where larger facilities have more of a
46:50
capacity to grow than smaller facilities and that was kind of what we were trying
46:55
to get at with with this chart in this metric is understanding how are all of these changes in the ASC industry
47:02
putting pressure on different pieces and different groupings within within the
47:07
ASC yeah I think this is just one of those metrics that everybody needs to be
47:12
looking at every year in order to to just track how your facility is
47:18
progressing financially I have a note here but especially if you’re seeking any external investment or Partnerships this
47:25
growth rate can be key as obviously investors are often prioritizing those
47:30
with consistent growth um it’s also interesting to see that the facilities
47:37
that have the higher number of ORS are the ones that are seeing um the most growth and obviously you know the ones
47:43
and twos and threes and fours are are can be struggling a little bit um you know depending on the growth rate you
47:50
can really make informed decisions on resource allocation you know do you need to hire more more staff do you need to
47:56
invest in new equipment do you need to expand this can really help and being
48:02
able to use this number this metric here in tandem with your O Block utilization
48:09
and what was that other the average revenue you can really identify where
48:16
your shortcomings are and and improve yeah and this is another one
48:23
where when you compare the um the average o and Recovery duration um what
48:29
we’re trying to do is we’re just trying to give you some metrics that you can help triangulate what are the levers
48:34
that you have to pull within your ASC to help you either grow or maybe if you’re um trying to perform you’re you’re more
48:41
focused on different aspects that are um within the ASC if it’s collections rate
48:46
or if it’s just trying to improve your reimbursements based on um the average net revenue that’s kind of the focus
48:51
here is we’re trying to start to paint more of that picture with data of where the opportunities within your ASC and
48:58
where other people having success that maybe you can um identify as opportunities within your
49:05
facility perfect so we do have a few minutes left so just a reminder if you do have any
49:11
questions at all please put them in the chat and we can hang around for a few
49:16
minutes but really the you know the core reminder here is that we are in this era
49:22
where data driven operations is really the only option and I hope that this kind of gives you a snippet of why
49:29
that’s true and the benchmarks and data points you can be looking at to make sure that you know to really use data to
49:35
inform your work and be surgically precise in how you operate um if you want to continue succeeding and
49:50
growing
welcome to this week in surgery centers if you’re in the ASC industry then you’re in the right place every week
0:08
we’ll start the episode off by sharing an interesting conversation we had with our featured guest and then we’ll close
0:13
the episode by recapping the latest news impacting surgery centers we’re excited to share with you what we have so let’s
0:20
get started and see what the industry’s been up [Music]
0:26
to hi everyone here’s what you can expect on today’s episode last week we
0:32
held a live online event with Will Evans will is the senior director of data
0:37
science and insights here at HSC Pathways and we spent an hour reviewing 10 of the most compelling clinical and
0:45
financial industry benchmarks from hst’s latest state of the industry report so
0:50
if you haven’t seen it we’ve released a state- of the industry report in late September and it includes best practices
0:57
keepy process steps over 125 kpi ideas and benchmarking data for every step of
1:03
the patient journey and for nearly every recurring administrative Duty as well we
1:09
are in an era where datadriven operations are really the only option and using data to inform your work and
1:17
being surgically precise in how you operate is critical to thrive and
1:22
surgery centers that embrace the shift will be the ones who remain on top so that is really why we wanted to take the
1:29
time to not only create the report but also dissect the top 10 key metrics that
1:34
came out of the report and help you Embrace this mindset and get started so if you have ever wondered what other
1:41
surgery centers are experiencing for average block time utilization case cancellation rates patient deposit
1:48
collection rates average net revenue per case now is your opportunity to get a
1:53
window into how you’re tracking and Performing hope everyone enjoys the episode and here’s what’s going on on
2:00
this week in surgery centers hi everybody thanks so much for
2:08
joining us this afternoon I’m Erica Palmer with HSC Pathways and I’ll be moderating the webinar today if you’ve
2:15
been to any of our webinars before you know my usual shiel but this webinar is
2:21
truly for you so we do want it to be as interactive as possible so please use
2:27
the Q&A box that any time if anything comes up and I’ll make sure that either will or I can address the question that
2:33
you have don’t be shy we want to get all of your questions especially with the data that we’re showing it is unique to
2:40
HS and we want it to be a discussion you know if you’re seeing different metrics at your surgery center let’s talk about
2:48
it all right so what are we going to do today we are in the middle of our our welcome and housekeeping items right now
2:56
I want to take a moment to introduce the report to you as as well um obviously
3:01
today we’re focusing on 10 industry benchmarks but those benchmarks did come from a report that we published uh last
3:08
month and then talk a little bit about why this stuff matters and then I promise we will spend the bulk 90% of
3:14
this hour um talking about those 10 key
3:20
metrics so I’ve already introduced myself um I’m on the marketing side at HST and then I’m super excited to have
3:27
will Evans with us today he is our senior director of data science and insights and we uh would not have been
3:35
able to produce a report like this or get into kind of the nitty-gritty of some of these data points without Will’s
3:42
guidance so really excited to have him with us
3:49
today um okay so if you’re not familiar with the report I’m going to put it in the chat um whenever I have a second and
3:55
then I will it’ll be a next week’s email um you’ll be redirected to the report when this webinar ends so I’ll make sure
4:02
that you have access to the report itself um but what we decided to do was
4:07
publish a report focusing on best practices and proven data for optimizing
4:13
ASC operations uh so it’s a pretty extensive report there’s over 45
4:19
chapters with a ton of different data points and most importantly a lot of kpis so we’re always you know
4:26
encouraging surgery centers and clients to focus on data and in with doing this
4:31
report we’re trying to give you some examples of how to get started um or if you already been doing it for years and
4:37
data is a core piece of what you’re doing um I would love your thoughts on the kpis that we shared um if you think
4:43
we missed any or you know just general feedback of really trying to get everybody started on the kind of the
4:50
data front here and the report itself has six key chapters we really tried to
4:56
look at the entire patient Journey from the moment the doctor and the patient decide yes we’re moving forward with
5:02
surgery you know all the way down to the moment where they are being discharged from your facility so we’re looking at
5:09
pre-day of service day of service and post and then we’re looking at the regularly recurring operations so what
5:15
should you be doing on a daily and weekly basis what should you be doing on a monthly quarterly basis and then an
5:21
annual basis as well so again I will send this report um but the 10 data
5:27
pieces that we’ll be uh looking at today all came from this report and there’s even more in
5:35
there okay so why why are we here why does this
5:40
data matter you know kind of where is the surgery center going so what we’re seeing across asc’s is that the world
5:49
has really changed from what it used to be it used to be a lot easier to manage things in an ASC um but you know things
5:56
are getting more and more challenging uh reimbursements are stagnant or even lowering uh in some cases competition is
6:05
increasing across the board more hospitals are getting involved and taking interest in outpatient spaces
6:10
than ever before there’s an increase in higher Acuity cases I don’t need to talk
6:16
to any of you about the staffing issues that are going on but unfortunately it doesn’t seem like there’s any end in
6:22
sight based on projected models so you know Staffing shortages how are we going to overcome that and then of course I’m
6:29
sure you’re experiencing just like Rising costs of everything across the board especially supplies you know the
6:35
economy is really taking a hit especially for asc’s so Precision is really the only
6:44
option here and the new game in town so when we’re talking to those um who are
6:50
most successful and the most profitable centers they’re really focused entirely on efficient
6:57
datadriven Precision operations so just like all of you you know are so
7:03
surgically precise in the operating room we need to take that mindset and move it to the business side of the house and
7:09
shift from imprecision to Precision operations and you know we’d be
7:16
Hypocrites if we didn’t prove this with data so we’re seeing that there’s actually a huge difference between those
7:22
that that take this mindset and those that don’t some are really succeeding and others are struggling to you know
7:29
not forget Thrive and grow but just stay in business so two metrics that we’re
7:34
really seeing a difference here on is iida so basically like earnings or profit margins for businesses and then
7:40
of course block time utilization which we’ll spend some time on today as well and when you really compare the average
7:47
to those who are in the top cortile or you know top 10% there’s a huge
7:53
difference and it might only look like 10 or 20% across both of these metrics
7:59
here but that could equate to hundreds of thousands or or millions of dollars of extra earnings which of course could go
8:06
towards all the issues we’ve already talked about Staffing supplies recruitment whatever your facility needs
8:12
and the difference can be really Stark and just reminder because I’m I know I’m moving quick you’re going to
8:18
get the slides you’re going to get the recording so you can spend more time with these numbers as
8:24
well so what are top performers doing that is performers doing that is setting
8:29
them apart there’s really six primary things here so being surgical with o
8:35
utilization and profitability you know looking at the numbers regularly that all we were just talking about and
8:40
trying to improve them you know doing things like physician Recruitment and having Physicians come inbound rather
8:47
than you having to spend so much time and effort trying to recruit outside Physicians they’re automating manual
8:53
processes we are trying to remove as much human intervention in manual labor and make things as simple and
9:00
straightforward and automated for you um of course evaluating individual
9:05
case profitability so that at the end of the month there’s no surprises there’s no Panic about what cases you took on
9:12
that ended up not being profitable you know at least you’ll have the opportunity to to say yes or no when a
9:19
case comes across your desk monitoring case mix and Acuity and then of course
9:24
for forecasting hiring needs and Supply needs
9:29
and this kind of thinking and this this strategic approach can really change
9:35
everything for every stakeholder that touches your surgery center so for your admins or the business office folks it
9:42
moves them from a good amount of reactive work or redundant low value tasks uh to being able to Pro be
9:48
proactive and work on higher value things uh for your clinical team it moves them away from doing clerical work
9:55
and gets them back to what they love which is working with patients and actually being able to use their degrees
10:01
to their full potential and skill set Physicians of course you know on the business side they don’t have to worry
10:08
about all the nuances and they can instead think about their patients and the business as a whole if you have
10:14
management groups involved you know it helps them go from delayed insights to benchmarking across the whole portfolio
10:20
and trying to identify patterns and then of course Financial outcomes oh the
10:28
goal but if it was as easy as all of that everybody would be in the top
10:33
cortile so we fully recognize that this is an extremely challenging place to get
10:38
to and if you’re lacking automation you’re missing data you’re having all
10:44
these Staffing challenges and you have limited time it’s going to be really difficult to get to this place so in the
10:51
data that we’re presenting to you today and kind of this mindset we would love you all to shift into it can really help
10:58
over overcome some of these biggest hurdles and then of course you know HST was purpose built to help you do exactly
11:05
that we really do strive to make data uh live at the core of everything we do and help you run Precision operations and I
11:13
hope that um by the end of this webinar with the data we’re sharing with you and the time we’ve put into this that really
11:19
comes across all right so enough of me for a
11:24
second let’s do a quick poll first question we’re going to do two polls today this is our first one what other
11:32
sources do you use for industry benchmarking I would love to know um
11:37
where else you’re finding your data and you know kind of what you find most valuable so I will give everybody about
11:45
30 seconds to complete this poll and then I will share all the results as well and while you’re filling out your
11:52
answers I did just put a link to the full report in the chat as well okay so I’m ending the poll sharing
12:01
the results hopefully you can all see this but um ASA great resource ASU
12:07
quality collaboration is another great resource I think it’s potentially underutilized they have a lot of great
12:13
clinical metrics um available awesome all right thank you
12:19
all so much for sharing all right so to the good stuff first metric we’ll be
12:25
talking about today is average block time utilization so will I’m going to hand things over to you for a second can
12:31
you help us understand how this data point was collected uh sure Erica so for this
12:38
metric in particular there’s kind of two pieces that you need to put together to be able to calculate it and so the way
12:44
that we went about this and fully admitting that there are multiple ways that you can look at not just block time
12:50
utilization but o utilization in general the way that we calculated this here is that we identified scheduled blocks
12:57
within HST and then we tied cases to that reserved block based on the
13:02
physician or group that scheduled the case so if a physician who is not part
13:08
of who is not the physician that reserved that block and is also not a part of the group that reserved that
13:14
block if they perform a case during that scheduled block time in that o we
13:20
actually end up considering that non-block time and so we didn’t count that towards this metric so this
13:25
specific metric is really just calculated by dividing the um associated with performing cases um
13:33
by The Physician or The Physician Group that scheduled the the original O
13:39
block and this is one I think like going forward in the future there’s multiple ways that we’ll look at it because we
13:45
we’ll look at block Time and non-block Time versus the scheduled block and then we’ll look at overall o utilization as
13:52
well and really we would want to understand how do all those three kind of metrics work together to give you a
13:59
holistic view of O utilization and block time
14:04
utilization perfect thank you yeah I think this was one metric that we’ve actually gotten a lot of feedback on so
14:11
far just because of the way we calculated it and and to your point the way others calculate it it can make a
14:17
huge difference in the number that we come to but I’d like to think if we were all sitting in a room together you would
14:23
all be nodding along at the sentiment that you know a surgeon might have every
14:28
Monday from 9: to 12 blocked for them and then most 42% of the time it ends up
14:34
sitting under unused which can be frustrating but it also is just a huge
14:40
missed opportunity for Revenue generation and we’ll reference this metric again when we actually get to um
14:47
our final metric which would be year-over-year growth but this could be a huge opportunity to generate more
14:54
revenue for the organization and you know some I put some tips in here to improve it I’m sure you all have a lot
15:01
more you could share but you know being able to share your o availability online
15:07
with office schedulers setting internal goals for Physicians and staff and just
15:12
educating on the importance of high utilization I think could be really
15:17
great ideas to get to increase this or lower the number of but when your o is
15:23
not being utilized and you know It’s tricky because of course it’s all in the
15:29
surgeon’s hands right if this is their block time trying to educate them and have a conversation with them as to like
15:34
you know at what point can maybe we let it go and try to get other surgeries in there whatever initiatives work but
15:40
improving this number is just a a critical component to increasing your
15:47
bottom line before we move on there’s two other notes I I do want to call out
15:53
about this one when you start breaking this apart by specialty you do see a
15:58
different variations in O utilization by specialty like we have some gastro focused ORS and asc’s where you see this
16:06
number really high where they’re up around 80 or 90% there’s also like pretty big
16:12
dispersion amongst that same the the the the gastro groups but if you drill in by
16:18
specialty you’ll see different variations and distributions of this metric and then uh the other thing is
16:25
this one in particular is a great lever as Erica mentioned uh later on we’ll talk a little bit more about it but for
16:31
identifying additional opportunities if there’s unused block time and you can publish that or you can release that to
16:36
other for other availabilities uh it just helps you understand more of your Precision
16:42
operations perfect I do have three questions for you so how do you and also
16:48
I should say for the sake of time we might have to skip some questions but we will absolutely save all of these and
16:54
reply to all via email uh if we can’t get to them live but how do you track utilization for
17:00
unassigned Block times we have an issue with that sometimes we have doctors that post a lot without assigned block time
17:07
we have a hard time figuring out how to capture that right now that ends up falling
17:12
under the the non-block time and so when we do the math on this one we basically
17:18
have a flag where you can include or exclude that and I’ll be honest I don’t think we have a great way of of doing it
17:25
yet that’s this is where we start to morph to thinking about overall o utilization but that’s definitely one
17:32
that I think as we go through this again uh for 2024 and we start to calculate some of these metrics that’s more of
17:38
kind of the Fidelity that we would we want to uh start to tease out definitely is block calculated by MD
17:47
scheduled time or actual patient in room time so the block is scheduled by based
17:55
on what the what the doctor is scheduling for for actual consumption of
18:00
that time there’s a hierarchy within hsd that you can go through where there’s at
18:07
at certain facilities do it in different ways and um I think if you have eart you can literally get the entrance and exit
18:13
times for the O but basically we step through a process of what’s the highest
18:19
level of granularity is it an echart based in andout time all the way down to what was just the schedule start and end
18:25
times for that case and we go through and we look at what gives us the best indicator and what we think is the
18:31
highest Fidelity data point to use thank you and last question I’m
18:37
hoping you know the answer because I do not how do you adjust for Physicians that have flip
18:45
rooms I don’t have a great answer for that one okay Kelly I’m saving this and
18:50
we will get back to you okay so let’s keep it moving to
18:56
metric number two so here we’re looking at insurance preo and verification rates
19:02
so will can you give us a little insight into this metric please sure I’ll start
19:07
with insurance verification that one’s a pretty straightforward metric here within HST we just went through and we
19:14
summed up or we counted all the cases where they had the insurance verification complete and so it’s a
19:20
simple just yes or no and we divide that into the the total count of cases that
19:26
had insurance or that either did or didn’t have insurance verification insurance pre-authorization it’s a
19:32
basically a similar methodology but for counting the yeses here uh we um include
19:38
multiple statuses there are some that don’t require a a pre-authorization to
19:44
be completed and so we have to control for that but uh the shortest way I think to describe this is where insurance
19:52
pre-authorization was not completed that’s anywhere where it’s a no or it’s a null value in the hsd system and so
19:58
it’s the same methodology you just sum up the yeses divided by the total base thank you first question how do you
20:07
know which procedures do not require
20:13
preo I actually don’t know that’s a good question that’s one to be honest in the
20:19
HST system the code that we use is NR and that’s where it’s not required but I
20:25
would have to talk to one of our internal product experts to to give you a good answer on that one sure and so
20:31
Emily we can definitely give you a little bit more insight there good question though and I think you know
20:37
with both of these metrics it’s it goes without saying that they directly impact your reimbursement and revenue
20:43
collection and ultimately patient satisfaction physician satisfaction so
20:48
really honing in on your processes and also trying to take out as much um human
20:55
component to it as well and making sure that you have systems in place where you can continuously run Insurance
21:01
verification you know not just once but whenever you would like to so as soon as you receed the case maybe the first of
21:08
the month you’re running Insurance verifications for all the cases in the upcoming month and then on the morning
21:14
of every day every morning you’re running Insurance verification for your procedures for that specific day and if
21:21
you don’t have an automated way to do that you’re uh going to spend a lot of manual time doing it or Miss cases where
21:28
insurance has lapped for multitude of reasons so obviously you know trying to identify trends when you are having
21:36
issues with this you know are there certain procedures payers are there time periods you know that you’re experiencing issu most issues with this
21:43
when um deductibles reset on January 1 or whatever it might be you know fixing
21:48
communication between the front office and the billing staff utilizing technology um adjusting documentation
21:55
practices and ultimately training staff too I think for me that’s just a big takeaway from all of this if you’d
22:03
haven’t had the opportunity whether it’s during a staff meeting or whatever it might be to really educate everybody
22:09
within the in the ASC walls as to the importance of all these metrics and why it matters I think that’s also just a
22:16
key like education is just a key piece of this too all right metric number three case
22:25
cancellation rate so we talk about this all the time we got lot of questions about this I actually saw a thread in
22:30
the askap form recently where someone else was looking to Benchmark you know see if where they were at compared to
22:36
their peers will can you tell us a little bit about case cancellation rate please there this is another one that
22:44
was it’s a pretty straightforward calculation where we’re just counting up the number of cases that were scheduled
22:51
in q1 and Q2 of 2023 but then were canceled and dividing that by just the
22:57
total number that were scheduled let me see if there’s if we had any caveats in here no I think it’s a pretty
23:03
straightforward calculation on this one yeah I agree and I I think this obviously it’s an easy one for people to
23:10
understand and an easy one for everyone to understand the impacts so you know obviously it impacts your bottom line
23:16
it’s frustrating for staff physician um and staff satisfaction but also patients
23:21
you know unless they’re the one doing the cancellation but you know this is another place where you can really
23:27
improve your by identifying the trends so is it patient related is it an equipment issue
23:33
is it just an unforeseen emergency what is it and then you know again T is it
23:39
around the holidays when are you experiencing your highest case cancellation rates year over-year so
23:45
that you can uh prepare for it you know automating patient text reminders and preop instructions so you never have to
23:51
cancel a case because the patient didn’t know they didn’t have to eat whatever it might be offering Financial counseling
23:57
so is a patient get arriving the day of and they’re seeing their bill and they haven’t seen it yet and they’re stressed
24:03
and they’re deciding you know they’re going to walk right out or whatever it might be obviously if you’re having
24:08
equipment issues you can hold more frequent equipment and supplies checks so first identify those Trends and then
24:14
you can really go from there all right patient deposit
24:22
collection rate this is a fun one will how did we get here
24:28
uh sure so this one uh within HST there’s two fields that we use to calculate this there’s the um it’s the
24:36
expected patient deposit amount and then there’s the actual patient uh deposit
24:41
collected um and so the math here is pretty straightforward um we’re just dividing the actual amount the actual
24:49
patient amount collected by the expected amount collected which on the surface is pretty easy to do for whole and an
24:56
aggregate but we know that the this isn’t used by all centers and so when we calculated this 53% number we had to go
25:03
through and um basically scrub out some of the data that um we knew wasn’t accurate and so generally speaking how
25:10
we did that was we looked for uh centers that just weren’t populating the
25:15
expected collection data and in some cases they were only populating it maybe very sparsely so to basically try to get
25:23
to a high fidelity number we would remove the the centers that aren’t using it or are basically not using it
25:29
reliably so that we could try to triangulate a number that we felt pretty good
25:34
about perfect thank you yeah I would love to hear in the the Q&A box too if
25:40
you know any of your numbers off the top of your head for any of the metrics that we’re sharing and you’re comfortable putting them in the Q&A I’d love to hear
25:47
them because this number 53% collection rate on expected patient deposits it
25:54
just seems so low and I’m sure everybody would want it to to be higher we do have one question will are you assuming the
26:01
center has the correct expected payment this number changes when EOB
26:07
arrives uh yes essentially what we’re doing is we’re trusting them to put in the
26:13
correct amount fully knowing that yeah this isn’t it’s never going to be 100% I think objectively accurate data and so
26:21
that’s why we’re kind of declaring the metric these are the basically the parameters that we’re using for it over
26:27
time I think this is some one that we can probably evolve and maybe change and
26:32
look at it different ways but yes perfect thank you yeah and I know
26:38
you know we talk about price transparency all the time here but a
26:44
very easy way or a very straightforward way I should say to increase this number is to send an accurate patient estimate
26:53
to the patient as far in advance as possible have it automated know nobody on your side should be manually
26:59
crunching numbers in order to tell a patient what they owe and they certainly should not be finding out what they owe
27:05
for the first time when they walk in the day of surgery so not only you know automate the process of generating the
27:12
estimate send it to the patient via text or email so that it’s you know no one can ever say to you I never receive this
27:20
and then also offer them a way to pay online have an immediate call to action
27:25
and offer them credit card payment online payment whatever it might be um we actually did have someone share
27:33
so Diane shared uh we use this as a quality study which is um a great idea
27:38
and we have went from 36 46 36 to 46% to sustaining in the
27:45
high 90th percentile so that’s extremely impressive if you would like to share
27:51
what you did to get to that number I’d love to hear it I’m sure everyone else would that’s awesome Diane thank you for
27:57
sharing that that so you know a couple ideas increase collections by automating
28:02
that cost estimation process internally and then of course just offering transparency at every level you know of
28:08
course you can do everything that you can patients are human so there’s that element to it but by
28:15
offering an easy way to pay in advance you’re just setting yourself up for
28:21
Success there this is this is another metric where when you step into it and
28:26
you look at the distribution of outcomes um you do see centers as kind of Diane
28:32
mentioned where they’re meeting 90% but like solidly into the 80s and
28:39
90% they’re collecting a really high rate on their expected deposits across
28:44
millions of dollars there it’s not just there’s a weird outlier where the center doesn’t do a high volume but they do a
28:50
great job of collecting on their deposits there are ones that are there are centers that are legitimately
28:56
outstanding at this that’s awesome something to strive
29:02
for okay so let’s talk about average o
29:07
duration and recovery time will can you share how we got to these numbers please I know they’re small again we’ll send
29:13
them out but sure sure so this one the math for kind of O duration and Recovery
29:20
duration is pretty straight forward it’s really just what’s the entry and exit times for the o or the procedure rooms
29:27
uh same thing for Recovery rooms and so it’s really just identifying what’s the
29:33
best metric what’s your highest Fidelity entrance and exit time and then subtracting that and averaging it out
29:39
the other piece for these is how do we map to how do we map the basically all the cases to Specialties and the
29:45
methodology we chose is to basically use the primary CPT code associated with a case and basically map that to to a
29:53
specialty and that requires some level of normalization within h not everyone codes all their Specialties
30:00
the same way or they don’t use the same abbreviation and so just you know when you think about it some Specialties like
30:06
ENT some of them are labeled as ENT with a three-letter abbreviation whereas others are they use Otto like
30:13
oenology and so we had to do some cleanup and kind of coding of the data on the back end to to map all the cases
30:20
to Specialties yeah Will’s being humble he really took one for the team here and
30:26
categorized all of our CDT so we can get to this nice clean graph here so yeah I
30:31
think this is it’s just really interesting to see and again you know within your own Surgery Center kind of
30:37
where you’re trending are o times and Recovery times increasing decreasing why
30:43
uh why is it happening because obviously the time you spent in the O and the recovery area directly influences
30:50
operational cost so by kind of understanding and optimizing the time in
30:55
the O and in the recovery every time uh you can obviously improve your bottom line but it also enhances the patient
31:03
experience increases satisfaction across the board and on the recovery time side
31:09
you know you’re really showing that you’re prioritizing the well-being of the patient which will lead to positive
31:14
clinical outcomes and of course Pat patient
31:22
satisfaction all right days to Bill bys
31:27
what do we have here will sure so this one um again there’s kind of two pieces
31:33
to how we um calculate this metric the first one uh days to Bill that’s a
31:38
pretty straightforward it’s uh really subtracting um the date the first bill was sent um from the the admit date or
31:47
the date of service and then you can average that over any number of basically groupings but the other piece
31:53
is how do we identify the number of ORS for an ASC and for that essentially what we did was we went and we counted the
32:01
number of unique o and procedure room names by facility and then using that we
32:08
were able to identify how many procedure and O rooms a facility had and we basically Bend those into different
32:14
groupings that you see on the bottom of the chart perfect thank you and I know this
32:19
was one we had gone back and forth on just because there’s so many ways to kind of slice and dice and look at this
32:25
data um but obviously number of ORS is kind of an equalizer that everybody can
32:30
look at and and relate to so obviously days to bill is just a key indicator of
32:36
the efficiency of your entire revenue cycle you know timely billing contributes to timely reimbursement and
32:43
it directly affects the speed at which your surgery center can receive payment so obviously the lower you can get your
32:49
days to bill the better optimize cash flow reduce the risk of delayed payments
32:54
there’s really there’s really so much here and I think by kind of refining the billing process if you’re not at a place
33:00
where you want to be or if you think you’re if you’re falling short in comparison to your peers here and you
33:05
want to maintain a healthy financial position obviously there’s a lot of things you can do to improve this but I
33:11
think you know investing there’s so many RCM companies investing in different Technology Solutions training your staff
33:17
improving communication between departments there’s a lot of different ways you can get this number down if
33:22
it’s too high and you know it’s taking too long to get the the claims out the
33:30
door we don’t have any questions let’s do claims denied what
33:37
what do you have here will uh this one’s pretty straightforward calculation here we
33:43
really just count up what are the number of claims that have a denial date or a denial reason and uh dividing that by
33:50
the total number of claims that we had processed during the q1 and Q2 of 2023 um this one this is one of my
33:58
favorite kind of metrics to calculate not just because it’s specifically telling in itself but very early on in
34:05
my career at hsd this was one of the first kind of correlations we found between authorization rate and claim
34:11
denial rates and that we saw as authorization rates increased claim denial rates tended to decrease and it
34:17
was just a it was a cool study in in kind of Predictive Analytics around understanding what are the
34:24
drivers of claim denials and uh being able to trace that back to things that happened kind of on the front end of the
34:30
revenue cycle and understanding just the interplay between different pieces yeah I think that’s great and
34:37
again if anyone has any if you know off the top of the head top of your head where you’re at in terms of claims claim
34:43
denials I’d love to see that in the Q&A just out of curiosity but you know this
34:50
obviously impacts the revenue cycle so much you know they a claim denial can
34:56
easily result in delayed or lost Revenue which obviously can affect your overall Financial stability it also can really
35:02
strain the relationship between your surgery center and payers so again if you’re trying to find the root cause and
35:10
and it’s you know you’re seeing a trend with a certain payer kind of building that relationship with them and asking
35:16
them and and you know having that conversation with them of like hey every time we submit this
35:21
one claim with these same variables we’re getting denied like what are we doing wrong how can we fix it really
35:27
opening up that dialogue can help as well and again you know when you do notice if you do notice an uptick in the
35:34
percent of claims denied it’s really time to initiate a deeper dive to understand that root cause is it a
35:40
coding issue documentation shortfall again a specific procedure that’s continually getting flagged and then
35:47
from there you can focus on staff training um software and technology so
35:53
consider using Advanced billing software that can help flag potenti potential denial triggers before you submit the
35:59
claim so you kind of have that extra level of Defense before it goes too far and that that alone can substantially
36:06
reduce denial rates of course regular Audits and then engaging with payers
36:11
would just be advice here if you do want to if you are seeing some some issues in this world so before we finish up I do
36:20
just want to send out our second and final poll I know we’re talking a lot so
36:26
would love to get get some engagement here here we go I’m launching the second
36:31
one here what is the biggest challenge you’re experiencing right now when it comes to analyzing data just give
36:39
everybody a minute and I know we have a lot of different organizations on the group or on the call so whether your
36:45
management group or an independent ASC or a consultant this all applies to you all right I’m going to end the poll and
36:53
I am sharing the results now this is always really interesting in to see so we’re looking at data quality yeah that
37:01
It’s just tough right whatever data goes in is the data you’re going to get out so trying to educate staff get everybody
37:09
on board here’s the importance of why we have to input all these metrics whatever it might be lack of expertise time
37:16
constraints data security and just not sure where to begin yeah I hope you know
37:22
with the report that we did produce if you’re not sure where to begin it can certainly look a little overwhelming
37:29
just because there are so many kpis and so many data points that are shared but
37:34
it could be helpful to at least pick one or two or three key metrics where you want to start and go for it all right
37:42
thanks everybody so next I’ve lost track I think this is seven seven sevenish but
37:49
here is average of days not worked by age of receivables so take it away will
37:55
sure so this is another metric where there’s a a couple different pieces that you we needed to calculate to create it
38:02
I think the first piece to tackle is essentially figuring out the age days and so to do that we aggregated accounts
38:09
with owed balances by their age by the age of the receivables so it’s essentially how old the receivables are
38:16
since their date of service or their admit date and once you do that you can average that over basically whatever
38:22
groupings you want and then we ident then to get to the the last date that
38:27
something was worked what we did was we looked in the HST system and we identified the last date that a
38:33
non-system generated note was put on an account and that’s not necessarily like
38:39
a clinical note or or something along those lines it’s it’s when was the last date that that account or that case was
38:44
being worked and then basically once you figure out that date you calculate the difference between today or the current
38:51
date and that last note date to identify basically when was the last time that
38:57
account was worked based on the age of that case and then you essentially just average those last work dates by the age
39:05
days and you bend the age days in 30-day
39:10
increments perfect thank you yeah this is an important one you’ve probably
39:15
noticed as we’re trending we’re getting into those recurring regular regularly recurring operations that should be
39:21
taking place on a weekly to monthly quarterly basis and this is a huge one
39:27
um because obviously the older receivable becomes the more challenging it can be to collect and you know you
39:35
can really use this data to kind of prioritize followup on older receivables
39:40
and kind of implement a systematic follow-up procedure that can hopefully reduce the number of days that an inv or
39:47
receivable becomes unworked and analyzing specific age buckets and breaking down like we have here the day
39:54
is not worked into specific time frames can help pinpoint where the most significant challenges lie and again
40:00
customize strategies for for each bucket and you know kind of goes back to
40:07
that patient deposit collection rate as well you’d like to think if you see an increase there you’re going to see a
40:13
decrease here and the more you can obviously collect up front the less
40:18
issues the you’ll have on the back end of things and of course delays can arise
40:24
simply by patients not understanding their bills so by try trying to increase the patient communication provide
40:30
Clarity on procedures costs and insurance coverages and then also trying to fix and automate some of the
40:38
procedures on your end as well in terms of Outreach can certainly help fix this
40:45
number we did get one question for the benchmarking as a whole can you share
40:50
how many asc’s were queried and is it in a specific location throughout the US
40:56
and then then is it a mix of Specialties as well sure so it the total Universe of of asc’s
41:04
that we pulled data for I think was around 450 I believe I don’t remember the specific number off the top of my head
41:11
but it’s right around that ballpark but basically it was centers that we have the rights to use data for benchmarking
41:17
purposes and calculating these sorts of metrics depending on how good the quality of data was at certain centers
41:24
we did have to filter some out and so there are certain ones like the expected the percentage of expected patient
41:30
deposits that number is going to be calculated off of a smaller base since we know some centers don’t really
41:36
populate all that data and they don’t really if we include those we’re introducing skew to that data set so for
41:42
certain metrics we did have to trim it down but kind of the overall universes right around 450 centers and it pulls
41:50
from it’s not all 50 uh States I want to say it’s 40
41:56
five but we did have coverage across we had coverage across 45 of the 50 states
42:02
some of the smaller ones we didn’t if we have centers there we didn’t have the the rights to use their data in these
42:09
calculations and then it is a mix of Specialties it’s I mean I think we see the Specialties on the uh on some of the
42:16
other slides but it’s we hit a pretty broad array of them
42:22
thanks okay there are no more questions about this one I will keep it
42:29
moving all right average net revenue per case tell us about this one will so this
42:36
one this is another one that we ma to Specialties and so for here we use the
42:41
same methodology where we identified the primary CPT code and we normalized Specialties and then mapped it over and
42:48
then for net revenue we’re looking at Contract fees and this is basically a straightforward just calculation of
42:54
averaging out the contract fees by specialty once you’ve mapped that over
43:00
one caveat I did want to make here is that I believe for pain we pain I think
43:07
is a little bit higher than average benchmarks you’ll see here and I think that’s mainly because this one ended up
43:13
having a pretty higher or a relatively higher um percentage of placement of
43:19
neuro stimulators in it and I know some centers I think that will end up getting grouped under different Specialties and
43:26
so just one caveat on this one that is one I think anomaly in that I want to
43:31
call out around how these numbers were calculated perfect that makes
43:37
sense yeah I mean this metric is key right it can really drive your entire
43:42
surgery Center’s growth strategy it really provides you know an immediate snapshot of the revenue that you’re
43:48
generating for each case a lower net revenue might indicate some operational inefficiencies um which could be due to
43:55
proed procedure times High Supply costs maybe inefficient resource utilization um so really understanding
44:03
the net revenue per case it can also leverage you can also leverage this during negotiations with uh payers and
44:11
make sure that you’re receiving appropriate reimbursement as well and
44:16
this is definitely one metric that we would really recommend incorporating into your periodic performance reviews
44:23
setting targets for improvement identifying areas that might need attention and then the big one would
44:28
just be assisting uh you in projecting your future revenues so help we make
44:34
informed financial and operational decisions which Specialties do we lean into it could really drive your growth
44:40
strategy you know I know everyone’s talking about total joints and cardiovascular right now and I know it’s
44:46
kind of hard to see but that’s number one and number two in terms of net revenue per case so this can really be a
44:53
key metric when you’re talking about 2024 and Beyond and if you want to grow if you want to sell whatever your
44:58
surgery Center’s end goals are this can be a really key metric to help you get
45:06
there all right and our final metric here will talk to us about the year
45:11
over-year net revenue growth sure so here this is another one where I think
45:16
there’s kind of two pieces there’s a couple pieces that we had to calculate to put this together the first one
45:22
number of ORS that’s it’s the same method ology we used on some of the
45:27
previous slides where we’re just counting up the number of unique operating and procedure rooms at a facility and then for year-over-year net
45:35
revenue growth essentially how we calculated that was we summed up the net revenue bu Center for q1 and Q2 of 2023
45:44
and then we divided that into the sum of net revenue per Center for or at a
45:50
center for q1 and Q2 of 2022 and we did this for Apples to Apples so basically
45:56
if we had customers that came online through the tail end of Q2 of 2022 and
46:02
they were they stayed on through 2023 for HST uh we actually omitted those
46:08
from the data set right because we’re getting a smaller denominator for uh 2022 that’s going to inflate that growth
46:15
rate for that Center and so um this is one where we did have to trim down the data set a little bit it wasn’t a ton um
46:23
but basically we’re really trying to get to an apples to app um calculation on the same cohort of
46:30
centers so that we can really understand what’s the year-over-year growth that’s happening in the ASC industry by the
46:37
size of the facility and these I would say like there are certainly ranges
46:43
around each of them like it’s but the overall trajectory is what you see where larger facilities have more of a
46:50
capacity to grow than smaller facilities and that was kind of what we were trying
46:55
to get at with with this chart in this metric is understanding how are all of these changes in the ASC industry
47:02
putting pressure on different pieces and different groupings within within the
47:07
ASC yeah I think this is just one of those metrics that everybody needs to be
47:12
looking at every year in order to to just track how your facility is
47:18
progressing financially I have a note here but especially if you’re seeking any external investment or Partnerships this
47:25
growth rate can be key as obviously investors are often prioritizing those
47:30
with consistent growth um it’s also interesting to see that the facilities
47:37
that have the higher number of ORS are the ones that are seeing um the most growth and obviously you know the ones
47:43
and twos and threes and fours are are can be struggling a little bit um you know depending on the growth rate you
47:50
can really make informed decisions on resource allocation you know do you need to hire more more staff do you need to
47:56
invest in new equipment do you need to expand this can really help and being
48:02
able to use this number this metric here in tandem with your O Block utilization
48:09
and what was that other the average revenue you can really identify where
48:16
your shortcomings are and and improve yeah and this is another one
48:23
where when you compare the um the average o and Recovery duration um what
48:29
we’re trying to do is we’re just trying to give you some metrics that you can help triangulate what are the levers
48:34
that you have to pull within your ASC to help you either grow or maybe if you’re um trying to perform you’re you’re more
48:41
focused on different aspects that are um within the ASC if it’s collections rate
48:46
or if it’s just trying to improve your reimbursements based on um the average net revenue that’s kind of the focus
48:51
here is we’re trying to start to paint more of that picture with data of where the opportunities within your ASC and
48:58
where other people having success that maybe you can um identify as opportunities within your
49:05
facility perfect so we do have a few minutes left so just a reminder if you do have any
49:11
questions at all please put them in the chat and we can hang around for a few
49:16
minutes but really the you know the core reminder here is that we are in this era
49:22
where data driven operations is really the only option and I hope that this kind of gives you a snippet of why
49:29
that’s true and the benchmarks and data points you can be looking at to make sure that you know to really use data to
49:35
inform your work and be surgically precise in how you operate um if you want to continue succeeding and
49:50
growing
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