Hello and welcome everybody to today's webinar. We're so excited to have you joining us. This is boosting orthopedic revenue, a data driven approach. So just a few housekeeping notes to get us started. All attendees are in listen only mode. So we'll be using the Q&A function to gather questions for our speaker. We're not going to be using the raise hand function. So please do submit those questions through the Q&A and interact with other attendees by posting comments in the chat. If you're using the chat function, just be sure that all panelists and attendees are selected from the dropdown message. And today we are joined by Russell Hendrickson, CEO and Scott Everett, MBA, VP of healthcare solutions from Practical Data Solutions. So I am going to hand it over to Scott and Russell to get us started. Wonderful. Thank you so much, Jessica. I appreciate it. So good day. I'm Russell Hendrickson and today's webinar, boosting orthopedic revenue, a data driven approach. We're so excited to have you here. Hey everyone. Thanks for joining us today. And just real quick, if you're unfamiliar with the Practical Data Solutions, we are a healthcare analytics company with more than 24 years in delivering healthcare analytics to organizations and orthopedic practices all across the country. So today we have a couple of objectives for what we're trying to, hopefully you walk away with today. We want to really talk about if we're going to make changes, we need to be kind of data driven in that approach and how we can apply our data analytics to find out where we are and help us to decide where we want to go. We want to help us to determine some strategies for how we can optimize some financial outcomes and ways that you can really start dropping revenue to the bottom line. And of course, we want to talk about how you can communicate that because communication is really the key by utilizing data visualization techniques and benchmarking and how that can really be beneficial for your practice. Yeah. So sort of speaking about visualization techniques, you know, a lot of people think visualization is, you know, putting a bunch of metrics onto a dashboard and certainly that's a piece of the puzzle. But what we're going to do is break down what are the right metrics? And then ultimately, you know, our goal, how do we boost revenue? So how do we use data and being data driven to try to boost revenue? So with that, let's talk about what does it mean to be data driven? Yeah. So when we work with organizations, we really want the term data driven to be more than just a buzzword. What we're really looking at is how are we using the data? Data should be a cultural thing. We talk about it in our meetings. We're utilizing it for all of the decisions that we're making, the initiatives that we're putting together, budgets and goals for the year. We're applying that data to find opportunities where areas that we're weak, where we need to get better, where areas that we're strong, that we need to promote better. And then when we do that and we put these strategies in place, we're utilizing the data to evaluate how well those strategies are working. And we're continuing to uncover more opportunities. It's not a one and done thing. It's a continual use. So being data driven, you know, Thomas Davenport many years ago in his best practice book about applying data to health care, talked about what we call analytical intensity. And that really applies to being data driven, where we want to move from what are these lower levels of intensity, like just summarizing data or trending charges, payments and adjustments and what we really want to do is move up to how do we apply benchmarks? How do we build relationships between data so we can start to correlate what's going on? And then ultimately, how do we use data to project better outcomes? And so you might ask the question, why aren't more organizations, you know, data driven? Why aren't they able to apply technology effectively? Usually it could be any variety of reasons from just not having enough staff, not understanding the expertise, not having a budget, you know, technology limitations, or, you know, even being able to work with outside vendors. But ultimately, it usually comes back to leadership saying this is important that we really need to make sure data is supporting the decisions we're making. Yeah. And really what it comes down to as well is balancing perspectives where in the past, we had kind of a management perspective where executives, physicians, we all thought we knew what was going on in the practice. And then we would take what the patients were telling us and we would try to understand that and what we really want to do to be data driven is to take those two perspectives and balance them out with what the data is actually telling us. And so we really need to understand that and be able to have appropriate and effective data and analytics to really understand what's going on in the practice. Now when we talk about these perspectives, you know, we're going to talk about dropping revenue to the bottom line. But one thing we really want to make sure is at the top of everyone's attention is really understanding that patient perspective. Look at your patient surveys, understand what your patients are telling you both online as well as through the surveys that are coming through for, you know, whether you're using Press Ganey or another company, listen to what your patients are telling you. This is a competitive differentiator. And really, if you want to talk about dropping revenue to the bottom line, if you're not listening to what your patients tell you, it's going to be less and less. Yeah, really good point. But so let's focus in now on the main core of what we're talking about today. How do we boost revenue in your orthopedic practice? And it's really three key areas. We need to either focus on more volume, seeing more patients. We need to work on improving our reimbursement, making sure we're getting paid as much as we can for the services we're providing. Or how do we get paid faster? So with that, let's jump right into the first area. How do we how do we focus on more patients through the door, Scott? Yeah. So, you know, obviously, you want to drop more revenue to the bottom line. You see more patients. It's really just business one on one right there. But the issue a lot of time comes is, do we have access to we have the availability to get more patients through? And it's not just the surgical piece that, you know, we can't do surgical in an orthopedic practice without getting them into the office first most of the time. So we need to make sure we have appropriate access and scheduling and we understand those patterns that are coming through. We want to make sure that we're doing the right thing and appreciating our referring physicians and that we're providing care that they're satisfied with as well. And then we need to look at, you know, individual providers. What can we do to attain RVU growth that way? And when it gets to that point, we need to start looking at growing the practice. Do we recruit more providers? Do we need to add additional locations, things like that to to really understand how we can drive growth within the practice itself? But it really starts with, can we get more patients through the door? Yeah. And so related to that, one of the biggest areas that you want to focus in on from a data side, from a metric side, of course, is looking at, you know, what are going on with patient access? How easy is it for patients to get through the door? And some of the key metrics that are kind of ideal, you know, looking that appointment lag, the very simple from the time the patient called and said, I want to be seen, how many days did it take to get the patient in to actually be seen? You know, arrival rates, you know, where we may or may not have patients that are canceling or no show appointments, you know, are we having to bump patients, you know, periodically? And obviously that, you know, with surgery and sort of emergencies that relate to orthopedics, we may have some control over that. You know, certainly those are things that we want to focus in on. And of course, we'll look at scheduling and utilization in the next visualization we're going to show here. Yeah. So let's take a quick look at a visualization. And you know, a lot of the key tools can show visualizations like this in a web-based format that's interactive, easy to use. This is, you know, something where what we're really trying to do is put together some metrics and try to understand the correlation and the interplay between these metrics. So you see down at the bottom, right, we have our third next available and our appointment lags. And I really kind of like to look at the differences between the two of these, where my appointment lag is kind of what did happen, where my third next available is what could happen. And if there's a disconnect between the two of those, we really need to understand why and what's going on there. Additionally, you might want to look at finding available patient access through, you know, your arrival rates and are there ways that you can maximize the probability of arrival versus a no-show or a cancellation. And then of course, I always like to kind of start with those session statistics that you see right up in the top center that shows us, really helps us understand what our available capacity is and where we're falling short. Yeah. And so, you know, obviously we're showing this in a web-based visualization. We'll talk more about that technology, whether or not you're using these kinds of tools, you can build reports similar in Excel. And certainly most of these metrics you can pull right out of your, you know, your core reporting out of your EHR. A couple of the areas that sometimes organizations may struggle with is the scheduling utilization. I just want to talk about that for a second, and we're going to talk more about capacity coming up. What we're trying to do here in scheduling utilization is to understand, you know, how much is the physician available to see patients and how much is actually filled within that schedule. So, it's a little bit of, you know, do we have capacity in the schedule? And of course, if we're showing some physicians with capacity and some without, that should then be driving and appropriately correlating to our lags and our third next available appointments. But capacity lately has really become kind of a key issue and we hear this a lot with organizations, you know, based on a number of physicians, you know, having retired through COVID and with some of what's going on with sort of labor shortages. So Scott, you know, what does everybody think is our capacity and what does the data tell us? How is there a difference here? Yeah, no, every time we go in and work with an organization and patient access and they tell us they have problems, this is what they think is going on, is that all of their provider schedules are fully booked, that they're all of the patients arrive, all of the appointments are scheduled, all of the slots are filled. And really, when we start digging into the data, we think this is what's going on, but this is what's really going on, is that we have available capacity that's out there. We just don't understand why it's not being booked. And there are a number of reasons that can really fill into that, but the goal needs to be finding out why are we not hitting those purple areas and what can we do? And a lot of times it comes down to, you know, what I consider people, process and technology, you know, from a people side, it's, you know, the provider practice patterns, how often are they in the clinic versus how often are they in the OR? We look at staffing ratios and how we're doing that where it may be something going on with the call center. If it's a process thing, we might look at appointment durations and are those appropriate for what we're scheduling and billing or looking at cycle times, how long are our patients waiting to see the provider while they're already in the office or a technology issue, which we find very, very frequently where there's just inefficiencies built into the way that the technology is building the provider templates with regard to how long they can get their patients in, their frame rates versus available durations, appointment durations and things like that. There's ways that you can find capacity that way. It's just narrowing it down, figuring out what's going on and then, and then making the appropriate changes, but you have to be able to look at that data first. Yeah. Yeah. So, you know, we, we talked about patient access. We could probably spend a whole hour just on that topic, which, which is not what we're going to do today, but ultimately by driving more patients through by optimizing our schedules, you know, I think about this all the time in a, in a 20 physician organization, if you could get everybody to increase their capacity by 5%, that's equivalent to an FTE, you know, so a very small increase in a, in an orthopedic group can have huge ramifications. But ultimately as we drive, whether we want to look at RVUs, right, so more patients are going to drive more RVUs or reimbursement, however you want to look at it. Here's a blended visualization that tells us a little bit of the story that if we start looking at our top performing physicians, right, and we can see these are physicians that are generating high RVUs. We still may want to be, you'll see front and center in this visualization, just thinking about and being aware of that patient satisfaction scores, because ultimately that may drive patients away from the practice. The second thing though, as we potentially look at the physicians that maybe are underperforming and maybe they have capacity, but one of the things we may want to look at with their scheduling is which physicians don't have a lot of patients in their panels or, you know, patients that they're regularly seeing. So maybe we have some newer physicians or, you know, again, there may be reasons for that, but ultimately, you know, what we're looking at as we're starting to correlate data, this is a higher level of looking at what's going on with scheduling, looking at the productivity of the physician, and of course, kind of keeping in mind patient satisfaction. But the two other metrics on this dashboard that we're going to talk about is how do we focus in on potentially coding, making sure that we're, we're maximizing our reimbursement on each visit, or how do we make sure that we're getting those charges billed quickly, which is the time to payment. And the second area, how do we maximize reimbursement, is what we're going to talk about is another way to drive more revenue. How do we make sure we're maximizing what we're getting paid? Yeah, and I know every time we start talking about maximizing reimbursement, everybody says that the payer contracts and, and I talked to a lot of people who feel they really don't have a lot of control over that, but you actually have more control over maximizing your reimbursement than you think. And it starts with accurate coding, making sure that you're capturing everything that you're doing, particularly if you're doing multiple procedure surgeries, if you're doing, you know, different areas, or you have co-surgeons that you're working with, making sure that you're appropriately coding that way. And in addition to that, we're going to talk about really the impact that denials have on your overall reimbursement rates that are out there. Yeah. So let's, let's dig in, you know, just you kind of touch on this, Scott, but, you know, focus on coding, obviously understanding how you're coding, understanding how the physicians are coding, you know, between each other. And we'll talk about then being able to not only understand the data, but to put some perspective to it, to be able to focus in on how is the physician coding against some benchmarks. And we'll talk about different types of benchmarks internally against their peers, potentially, and externally against, you know, other practices or other industry benchmarks, you know, be benchmarks available from the, you know, from different associations, or even CMS. So ultimately, our coding, if we can make sure that we're, we're maximizing our reimbursement will drive, you know, getting paid more. Yeah. And again, like I said before, denials is a huge issue. And especially we find in orthopedics that, you know, you can be anywhere from five to 20% in your denial rates. And when you think about it, you could have the greatest contract in the world. And if you do, you have to subtract out the denial rates that you that you're getting as far as what are you what's your total reimbursement, what we've really finding is that while these denial rates may be 10 to 20% in some organizations, only about 35% are being appealed, there's a very, very low recovery rate. And so that's what's really driving down a lot of your reimbursement is you're just not getting what you're entitled to receive. And a lot of it comes back to denial. So ways that you can work denials effectively is by really starting and looking at what is it that you in your organization can control. And so, ways that you look at it is say, you know what, we have a lot of control over registration and authorization processes. We can collect the correct information. We can work ahead of time to get prior authorization and things like that. There are certain things that we do well, which make these denials not only preventable, but also very recoverable. But then there are some that we don't have a lot of control over where we're talking about medical necessity that hits or maybe documentation requirements that if we know ahead of time, we can work on prevention efforts, but we really don't have a lot of input as to what those requirements are. So, when we see these high impact and low impact and can separate it out, we really want to focus prevention efforts on the low impact areas. And then the high impact areas are the ones where we want to prevent those as well. But when we can't, we want to make sure that we're working diligently to recover as much of those as much as we can. So let's go ahead and take a look at a visualization again. You may not have something that puts all the pieces of the puzzle together around what's going on denials, but certainly, you can run different reports to look at some of these measures. Some of the key things that you'd want to do, obviously, is look at denials by your subspecialty, look at and understand where are we getting the most denials, where are we getting the most denied charges by payer, you know, or payer category. But then being able to categorize the types of denials into things that we can control, high impact versus low impact, being able to group denials into categories really gives you a different perspective as to what might be going on with denials and starting to understand it. One of the harder KPIs to measure, though, but is really critical is, and we talked about this, is this denial recovery rate. When we get a denial, did we ever recover on those services and for which procedures, for which physicians, for which, you know, specialties, and then ultimately, you know, for which payers, understanding what's going on with recovery of denials can even help focus our recovery efforts. Yeah, I think it's important here to look down. Sometimes you want to get down to that procedure code level and you can see if there are particular codes or there are surgeries or there are certain things that are being denied frequently or these things that you need to look at or work with your payers on, especially if you see particular procedure code payer patterns come together. These are things that you might want to look at and work with your payers on. And then other areas where you're looking at what's actually at risk if we don't recover this and what are the cash ramifications of not doing all we can to try to recover that denial that's out there. So a lot of good information that you have with denials. It's just a matter of focusing your efforts around it. Yeah. And so then obviously, Scott, you mentioned, you know, payer contracting and, you know, I've heard the same thing. You know, we have very little control over the rates that a payer is paying in our market, especially if we're a sort of a small orthopedic practice. But, you know, to me, the first thing is, you know, data is power. Data is knowledge. So understanding, are you getting paid according to contract? There could be opportunities there. Understanding your denial rates, because ultimately if you're getting denied and not recovering, there's a direct impact on the actual reimbursement versus what the proposed or contracted reimbursement might be. So as we look through being able to have data, even if you can't control it, at least understanding when we're seeing this percentage of patients, you could potentially even adjust your cash flow and your forecasting to at least understand. So to me, having the information is key. In addition, though, there's a couple of metrics right across the middle of the screen here that are the next area that we're going to focus on, which is understanding if we're getting denials, how long is it taking to recover? That's going to impact our cash flow. Understanding are the payers paying quickly? How long is it taking to get paid? And, you know, we can even measure them against contract, but ultimately understanding how long is it taking to get paid? How much money is sitting in our AR really ties into the third area of driving revenue and boosting revenue in our practice, which is how do we maximize cash flow? Yeah. Cash flow is really a critical piece that we look at when we're talking about driving money to the dollar, to the bottom line, because we've got so much tied up in different areas of our system, whether it's getting our charges into the bill or getting our billing out to the payer, getting the payer to pay back, and then any kind of backend collections that we have, whether it's denials work or collecting on the patient side of things. All of these are ways that if we can cut, the way I like to think about it is we can cut a day out of just one of these processes. This year, we'll collect 366 days worth of payments rather than 365. And that's a huge thing in terms of being able to drop things to the bottom line. So, you know, if we look at it graphically, you can see you have money at your bottom line and you have money tied up in your system. If you can shorten the amount of time that your total system looks at, whether it's one day, two days, it's a significant amount of dollars that drop to the bottom line where, you know, I always used to say you can't pay a salary with a receivable. This is something that if you take it and cut those down, that's dollars that are sitting available for use for the practice. You know, Scott, I always remember a story you told me many years ago where you're just focusing in on the charge lag of one department, you know, yielded something like just by reducing a couple of days, you yielded, you know, $450,000. You know, it was a significant impact to our radiology bonuses for the year. It was a it was a big deal just just by how long it takes to get the charges into the system. So you know, what's key here, right? So we talk about this is to be able to understand where we can improve or to measure improvement requires that we're able to benchmark. Right. And so we've shown a couple of benchmarks through and we're going to look at a few more here. But ultimately, benchmarking is critical to being data driven, because if we don't understand where we're at, so using internal benchmarks to understand where we performing or where we want to set targets, we want to reduce our charge lag, we want to minimize the number of days we want to be able to focus in on those in the organization that maybe aren't performing to where we want to be targeted. So whether it's, you know, appointment lags or contribution margin or overall productivity, whatever those internal budgets of any of the KPIs we've talked about having internal benchmarks give us something to measure to. And of course, then as we look at external benchmarks, like those available from the AOE, CMS, HFMA, MGMA, there's just a number of different places that benchmarks are available, right? Ultimately, benchmarks allow us to compare how we're performing against ourselves, how we're conforming against others externally, what would be considered best practice. And we're going to talk now about predictive benchmarks and what could happen. Yeah, and so really looking at it, there's an appropriate way to apply benchmarks as well, because a lot of times you can get internal resistance when you start putting benchmarks in your report. And what we have to understand is we're benchmarking to apply context, where we're saying this is where we are versus where we want to be. So we're looking at targets and the way we like to talk about benchmarking at PDS is we generate light, not heat. We're just trying to show where we are and where we're trying to go. We're not attaching any embarrassment or punitive measures to something like this. So when we look at benchmarking, obviously that's a key step in moving forward. We've even talked a little bit about the relationship analysis and seeing the correlations to try to get us up to that highest predictive projection level that's out there. But let's take a look at kind of how these relationships work and the interplay between them and how it kind of focuses back on what we've been talking about. So you can see here, this might be a standard dashboard that you would see in an orthopedic practice, where we see the focus on those volumes, where we can see our patient visits, we can see our surgery mix and where we're focusing surgically, where these surgeries are taking place, what are the top procedures we're working on. We can even look at what's scheduled out into the future from a volume standpoint. But one of the things that you might see and notice on here is right top center, we're also looking at patient satisfaction. That's a key area that we want to maintain focus on, balance that perspective, because really any future volume is going to be highly dependent upon that number. Yeah. And, you know, as we talk about this, I'm sitting here going, if you look over on the left side, you can see our new patient rate, and we have a benchmark, just a context compared to last year. We can see our referral rate, how we're doing against that. Here's that appointment lag. So sort of all front end focused. Scott, what I think we're missing here is I would love to see a patient sat ease of scheduling, you know, where were we last year or last six months, right? Some comparative benchmark just to understand performance. So probably something we need to add into this, this dashboard. But thinking about then, so that's volume driven, thinking about the next piece, how do we maximize reimbursement, right? So orthopedics, we have a lot of these ancillary services that provide quality of care to the patient, but also ultimately drive revenue, right? So thinking about what's going on within our PT practice, you know, how are we seeing volume in PT, being able to break them out and even looking at, are we potentially feeding our PT, not just internally with our own referrals, but potentially from outside in the community and where are we performing surgeries? So, you know, PT, obviously a key revenue source, obviously testing radiological procedures, being able to stand, are we growing there? Do we potentially need more equipment or maybe we have something strategic decision to make about releasing, you know, some of the machine or the equipment that we have. And then, you know, even looking at things like DME, you know, and what are we using and looking at the margins on that. So sort of focusing in on the reimbursement of our ancillary services, some key ideas and metrics going on here. Yeah. And obviously we want to break it down into the financial piece as well, where we're looking at, you know, charges, payments and adjustments, where are we seeing the volume trend that we would expect based upon, you know, our providers and our targets and our budgets. Are we looking at payments and adjustments together compared to our charges to understand are we collecting our collection rates appropriate to what we would want to see to maximize that reimbursement. But then we can also look at the cashflow statistics that are out there, where we look at average charge lag. We look at our days in AR and the management that we have of those. We can even add benchmarks that you see there or targets of where we want to be with regard to our charge lags with regard to our days in AR. And how are we performing? Are we above? Are we under? Are we close? And making sure that if we find a period where we're significantly different from that, that we're working to correct it immediately. Yeah. Yeah. So in the interest of time, the highest level of the analytical intensity is being able to project performance. And so I'm going to go back to initially we looked at patient access, right? And the real question here would be, can we do something that is simple as what is the volume of patients being seen per session or per hour? And these are our top performing physicians. These are our bottom performing physicians. We built in just the average or median. So we're benchmarking against ourselves internally. When we then focus on these are our best performers, these are our bottom performers. If we could just focus in on say the bottom 20%, we're using our data to identify the bottom outliers. Can we somehow model these outliers to improve? And if we could move the bottom 20%, just up to the median of the group or the average of their division, how much more revenue might we project could come in, right? It's not actual revenue. It's projected. If we could just move them up, you know, 5% or 10%, if we could just move everybody up a little bit, we can oftentimes project sort of significant gains. The old focus on the bottom, move the bottom 20% up, and we often can make significant differences to the bottom line. So with that, we just looked at a visualization many of you are familiar with. The tools have become very popular today, tools like Power BI, Tableau, et cetera. And so dashboards really help us tell a story, whether we're doing them in Excel, like some of the orthopedic reports we just looked at, or using interactive visualizations, but they should really be a key part of your analytic strategy. And so I encourage you, as you think about it, and you've watched today's presentation, do you have the appropriate access to data? Are you applying benchmarks? If you're not sure where to start with benchmarks, are you applying internal targets or goals? Do you have automation behind your data visualization tools? And, you know, do you have a clear set of KPIs that you're managing towards and focused on, and then allowing those that need information to be able to self-service to their data? Ultimately, are you driving a data-driven culture by providing data, or you're somewhat stifled because you're not sure where to begin? And I really think the keys that you had there, Russell, are access and self-service, where, you know, the reason we're using data is because we're trying to drive change. We're trying to move in a direction we want to go in, and so we need to make sure that we have the data to see that we're doing the right things, as well as, I need to be able to get my data myself if I'm a manager that's trying to manage to these standards. I don't want to have to be able to go and ask for someone to provide this data for me. I need to be able to see it on my own and dig in as much as I possibly can. Now, I know we talk a lot about becoming data-driven, and the fact of the matter is, when you start pulling a bunch of metrics together, it can get really overwhelming of, how do I manage all of these things? I need to manage patient sat, productivity, access. All of this becomes really overwhelming, but the way you look at it is not as a three different silos. You're looking at it as a whole. All of these metrics work together. All of these metrics support each other, and I think what you find is, at the end of the day, really, if you're doing what's right for the patient, all of the other stuff is just going to fall into place. With that, in the interest of time, let's jump over to questions here. Obviously, some of you, please chat in your questions if you haven't here, but some of the keys to success, obviously, KPIs, focusing on those three key areas, leveraging benchmarks, and then really driving the data-driven culture. With that, I see at least one question here. Will the slide deck be available? I believe the slide deck will be shared on the chat here as we're ending the session, as well as I believe it is up in the AAOE portal. Do we have any other questions here? I'm not seeing any other questions at this time. All righty. Well, you can absolutely rewatch this recorded session in the AAOE Learning Center. As soon as it is ready, then it'll be there. Oh, you know what? It looks like I sent that as a direct message instead of to everybody, so let me go ahead and drop again that link in the chat with the slide recording. Go ahead and click that link. That is the slide deck here. Again, it will be available along with the recording in the AAOE Learning Center. If anyone has follow-up questions, you can feel free to reach out to Scott or Russell. If you didn't grab their email address, reach out to me, and I can connect you with them as well. Thank you so much, everyone, for joining us today, and thank you to Scott and Russell for putting together this great presentation with lots of information. We look forward to seeing everyone next time around. Okay. Thank you so much. Thanks, everybody. Thanks.

Orthopedic Revenue

Data-Driven Approach

Practical Data Solutions

Patient Access

Reimbursement

Benchmarks

Data Analytics