Hello, everyone, and thanks for joining me for Medical Practice Operations, Business Fundamentals 101. We are in Module 6 today, where we will discuss healthcare IT and related issues. As you know, healthcare technology is playing a variety of different roles in healthcare, and as such, there are different platforms out there, and we will get into really, again, as with all the other modules, a macro look at what goes on and try to give you a macro understanding so that you are up to speed, at least broadly speaking, with regard to IT components and some of the foundational aspects of healthcare IT. As with our other modules, today will be 30 to 45 minutes, and I do appreciate you joining me and hope you get good value out of this today. I have nothing to disclose. This presentation, as per the others, is not legal advice, should not be construed as such. Any decisions involving legal aspects of healthcare should be vetted via qualified legal counsel. So, if it's signing an employment contract or a compensation agreement or getting into a murder and acquisition situation, what have you, I know enough about those things to understand them, but I am not an attorney, and I will not provide you advice relative to those things. This is AOA's disclaimer, which I'll allow you to read at your leisure, and a little bit about WIPFLY. WIPFLY is an accounting firm, a little over 100 years old, about 105 years old, and we service clients with accounting, audit, tax planning, those types of things in a variety of different business firms. As you can see from this slide, we do healthcare, agribusiness, construction, real estate. I am in the healthcare space. I manage our physician operations nationally, and for all intents and purposes, physician operations is really what I do on a day-to-day basis, are the component pieces of what we discuss in these modules. So, a little bit about me, more micro perspective, 30-plus years, coming up on 33 years in healthcare. I, as I said, run the national physician enterprise for WIPFLY. I do work in a variety of different healthcare delivery platforms, academic medical centers, rural clinics, FQs, federally qualified health clinics. I've done work with tribes. I've done de novo surgery center builds. I've done surgery center refreshes, if you will. I've done SNF work, private practice work. I've worked with large MSOs, which is management services organization, et cetera, et cetera. So, I've touched a little bit of everything in my 33 years, and I am specialty agnostic. And as I hope you've learned if you've listened to some of the other modules, really the care delivery aspects or the operational pieces in the ambulatory space are about 80% generic, right? There are policies, procedures, checks and balances. The nuance in the space would be specialty. So, generally speaking, internal medicine, cardiology, and the outpatient space are going to be handled pretty close to the same, except you might have a nuclear camera in a cardiologist's office. You're going to have some other CPT codes that you bill. You might do some carotid dopplers or some other ultrasounds, et cetera. And so, that's where the nuance comes into play. But as you recall from my many slides, and I think I have inserted that slide again, the ecosystem is fairly the same. And so, without further ado, we're going to jump into module six, the healthcare IT. We'll move on to module seven, coding, which I think you'll find interesting. We've skirted around that a little bit and touched base on it a little bit with regard to how we start to work our views and how CPT codes are crafted and how the reimbursements are crafted vis-a-vis Medicare. And then, if you've listened to the other modules, as you know, we will be doing a module eight in May, which will be live, and we'll talk a little more about that later. So, the learning objectives – oh, forgive me. I have coding up there. I will adjust that slide. The learning objectives for today are really to give you a good understanding topically of healthcare IT in the clinic setting, and we'll do a little bit of history, at least my history in the space. I will tell you that I know enough to be dangerous about healthcare IT. I've done work in a variety of different spaces on coding of healthcare programs of implementation. I put my first EMR in 22 or 23 years ago, so I know what that looks like. I know the pain that goes into that, and I know how those can be successful. So, we'll get into all of those pieces and just show you kind of what it looks like or discuss what it looks like and then give you a sense of kind of what the foibles are and where the landmines are. As with the other – the intention of these modules, this is not to get into the weeds of which EMR is best or, you know, clinic flow with regard to EMRs. It's really just to give you a sense of the good, the bad, and those pieces that I've experienced over the course of my 33 years in the space. So, here is, as per the norm, my clinic ecosystem, and with this ecosystem, on the left-hand side, we contemplate some of the IT component pieces that come into play with the care delivery space and the outpatient setting. So, at the front desk, you're going to have – and what I will call this is an integrated practice management EMR system. When I was a kid, what we had was standalone practice management systems, and we didn't have EMR. So, the PM system was for coding, billing. We did no data – well, there was a little data management. I hate to say I was geeked out on data back in the day, so I did a lot of data management myself, but there weren't these really glossy, cool reports that you could craft. Practice management systems in the day were built by, I would assume, engineers and coders who then would deliver a product out of the box that they thought gave you the tools you need to run a medical clinic, and what I learned early on is they didn't give me any of the tools that I needed as an operational leader, a non-clinician. I did not get the tools that I needed, and so, as practice management systems evolved over time, the reporting systems became more nimble. They became ad hoc. A lot of instances, you could craft your own, and people started to realize the value of data. So, when I say fully integrated, the EMR system I put in in 2001 or 2002, that was a fully integrated system, and what that means is the EMR and the practice management system, the business system, talk, for lack of a better phrase. They communicate with one another seamlessly to the clinician, so again, when I was a kid, you did all your billing stuff on the practice management system, and there was no EMR, and then, there were a lot of EMRs that evolved that didn't talk with the practice management system. So, you do one thing in one place, one in the other, and you can see how inefficient that would be. Then, the EMR, really, there are tools and gadgets in EMRs that you can use for operational flow efficiency if you deploy them and utilize them well. So, you know, back in the day when I ran clinics, when we had a patient ready in a room, we had a color-coded flip thingy, I don't even know what you'd call them, they were little plastic arms, and so, as the workup happened, and then, like, an MA would leave the room, they would push for the doctor, flip out, say, a green tab, so the doctor knew that room was next and ready. In EMRs, that sort of logic has been baked into some of these EMRs to show patient ready, et cetera. Not only that, a lot of these EMRs will enable you to track the data from the point the patient, the patient gets into the clinic and checks in all the way through the care delivery and how much time they spend in each of those stations. So that can really help in understanding the optimization and dynamic of the clinic and how efficiently or inefficiently we are performing our clinical duties. And then the finances, even in an integrated practice management EMR system, you know, it's going to be practice management heavy, so it's going to be the rev cycle, it's going to be all your CPT codes, all the data elements that you use to negotiate your contracts with payers. Again, I would go as far as saying, you know, skip down to marketing, I'll come back around to that. But for HR, again, you can use the PM system. You might have a bolt-on system, so bolt-on, that phrase in the space is how it sounds. In other words, I've got an EMR system that is off some server or some cloud-based computing, and then I've got a practice management system, and oh, by the way, I've also got a human resources component that's bolted on that handles all my HR-related stuff. Or that might be outsourced to a payroll company or to a company that specializes in human resources that, you know, what you would hope, and this gets back into our P&L, is that maybe you farm that out because an HR company that specializes, maybe they can do a better job at it at a lower cost than you can if you try to manage this in your own shop. So that's some of those decisions outside of the IT piece. And then data and analytics, I was alluding to, which also can drive marketing is, you know, are we going to introduce a new care modality in the space? If we are, we need to understand it can't just be, you know, I want a new echo machine in the space. Well, an echo machine costs money, obviously, and then there's all the warranty-related costs on top of that, and then there's staffing, and then where do we put it in the office? So understanding from a new modality perspective, what we're going to do with it, what will the fixed cost be, and then what are the variable costs? You know, are we adding on some sort of dosing that has to come into play where that is a variable cost that will be based on the number of studies we do, you know, 10 doses versus 100 versus whatever. So that varies with the number of patients. And so what you would do is, let's go with modality X. New modality came down the pike. Someone came back from their annual meeting, and there was a presentation on this X, and it can help with Y. Okay. So what I need to understand in my analytics, I need to run all of the patients I have who have a diagnosis code with whatever that is that could be patients for product X. And then I need to understand, and I believe we covered this a little bit in an earlier module, but then I need to understand, who's paying for this right now? Medicare paying for it? Is Medicaid paying for it? Are the blues plans paying for it? We can understand what the prospect of generating revenue can look like. And if it's just Medicare, which I installed a new modality in one of my practices a couple decades ago, Medicare was our only payer at the time. So we knew, based on our Medicare population and based on the diagnosis codes and what the modality is built for, we understood what our worst-case scenario would look like if we bought the machine and if we, let's say, we were able to get 25% of Medicare patients into using the machine or something like that. So you can start to make very conservative arguments as to how those tools can be utilized, but understanding our data, and I have said this before, healthcare has historically been awful with data management, data understanding, data utilization. And understand me when I say, this is not to say just get patients through the door. I'm not an advocate of volume for volume's sake or for revenue's sake. I am an advocate when quality of care can be coupled with efficient delivery of care. So if you could see 50 patients a day and you deliver the best care on the planet, why wouldn't you? So I just want to make sure everyone understands my caution as a businessman and as someone who's been in the field forever and has family in the space, I don't want you seeing patients to generate revenue. And I know and have seen physicians who do that. I want you to see physicians and people like me try to optimize your delivery space so that you can deliver whatever you define as quality of care to the most patients you are comfortable seeing. So that's a little bit of a side. The data analytics will drive some of the marketing. And then likewise, when you build out your strategy, you're going to take your data and analytics and say, okay, we want to put out an office, a standalone location 50 miles from here. What does that look like? Well, there's under, let's say we're a cardiology practice and that area is underserved in cardiology. Okay. I want to have a presence daily. How much is it going to cost me with a physician out there? I'm going to have to have an IT backbone structured so my systems can talk. And then I'm going to need to understand what does that market look like for me? Is there a hospital nearby where I can do caths or EP procedures, you know, understanding and using your data and analytics from your practice management system and marrying that to the market demographics is essential. And then reporting and PM. We've talked about the value historically, the value of looking at our data analytics, knowing what our key performance indicators are. And we'll dig into those in a little more detail. So as I noted, this is a broad overview to give you a history and some definitions. So that when people start throwing these crafty little acronyms around, you have a good understanding at least of what the, what the verbiage is contemplate that healthcare it and the delivery space and then noodle a little bit about the EMRs. Again, I'm not going to tell you what EMR to use. I don't have a dog in the fight. I don't get paid to recommend EMRs, but having been in the space and seeing them evolve, I do have a pretty good understanding of which ones seem to work well in which settings. So healthcare has as long had access to data, but we've been loathe to effectively understand and manage the data. So we have all this care delivery stuff that's been going on and candidly, when we were on paper charts, and I will tell you this, I do know of a few health systems that are still on paper charts in 2023 in any event, when we were on paper charts back in the day, you know, the physicians, the clinicians, the extenders or APPs, they just needed to see the patients and wanted to see the patients. And I understand that they didn't, they couldn't be bothered with aggregating data. And it was, you know, one visit, the care delivery plan for that patient, and then onto the next patient. We talked about the definition of fully integrated, and really, if someone tells you something is fully integrated, whether it's an EMR, PM system, which most of those now are, but when they speak to like, full integration of a, I don't know, of a lab service or something like that, ask them what that means to them. And I'll give you an example. When I put my, my first EMR in, we worked on an HL7 interface, which I don't, I don't even remember what HL stands for, I think it's hypertext language, version seven or something, I don't know, in any event, so an HL7 interface, where our computer would talk to the labs that we refer to. And then they would talk back to us when, when the labs were processed, right? So painting a picture, my RN, or my doctor point of care lab ordering, that goes out to lab company number one, they process the lab, and they, they send the results right back to my EMR. So then to close that care loop, I have a nurse who managed all of the outgoing orders, and then looked at all the incoming orders to ensure, A, what we ordered got, got loaded into the patient's charts, and then B, look for anomalies in the lab results that maybe required urgent re, recheck or, yeah, established patient, so recheck. So those things happen. And for me, after we got all the kinks worked out of that, that those, for me, really definitionally were fully integrated. They talked back and forth, I didn't have to do anything. And if you don't have to have human intervention, aside from my nurse ensuring that there was care follow up, short of that, I wouldn't consider something fully integrated. We talked about practice management systems, so people call them PM or PMS. And then EM, I still say electronic medical record, just because I grew up saying that. EHR is kind of the vernacular, but for me, they're interchangeable. I don't, I don't parse between them. And then a VPN is virtual private network. That is basically a pipeline that keeps your communication secure, especially if you're getting on a Wi-Fi network, where you're employed, they might have a VPN you have to log into, which will, which will protect your information. The last thing you want to do is be at a Starbucks working in the morning before whatever having cases or patients, and then be emailing back and forth on their Wi-Fi without having a VPN. Very dangerous and very unnerving for people like me. We talked about that, and again, the reasoning behind that, all these things link together, so the schedule info is available, but that's probably sitting on the PM system, but the two coexist, the PM and the EMR. The healthcare IT, this is not overly analytical, but things we talked about. The practice management systems will help you negotiate with payers, we're gonna get into that a little bit in finer detail. Quality measures and monitoring, whether you believe those are being deployed right now with Alacrity, or people are just talking about quality of care, you can manage those via your practice management system, or a bolt-on, again, if something you can put on that will talk, might work as well. All the production reports, revenue cycle, provider production, overhead management, those types of things, all are being driven by your healthcare IT, and then we talked about marketing and value-based care, and I'll give you just a couple of my absurd math models that I want to do, and we'll talk through how that works. Handful of market leaders in the EMR space. Everyone out there knows Epic, they are the 800-pound gorilla. To my way of thinking, really good product, and that's probably why they are well-known. These are just some of the bigger players in the healthcare space. Oracle Cerner, which used to be just Cerner, Meditech, Allscripts, NextGen, eClinicalWorks, some of them are out there to satisfy different market niches, if you will. eClinicalWorks, or ECW, was originally driven to satisfy the medical record, EMR needs, of smaller medical practices, right? So if you had a five-doc practice, you're not gonna buy Epic just because of the price point, and candidly, Epic is not going to sell to a five-doctor practice, that's just not in their bandwidth, and anymore, they wouldn't even pick up the phone if you called, or they wouldn't return your call. ECW, in its genesis, was built to fill that void. And so also, I do work in rural healthcare, there are some rural products that are really focused on and geared towards that rural marketplace. So you may get into a space, or a specialty, I'm dealing with a large orthopedic group, and they are using an EMR that is specifically geared towards orthopods, orthopedic surgeons. And candidly, the first EMR I put in was a cardiology platform designed by practicing cardiologists, and one of the reasons we picked it was because I knew my physicians, and I knew they were not gonna take time to build out the tools they needed to really utilize the practice management system. So instead, we went with one built by cardiologists, for cardiologists, and it had all the proper bells and whistles, so our maintenance, our management on the front end, or creation of templates and things of that nature, was really mitigated by that fact. And as luck would have it, that became a real preeminent medical record system in the cardiology space. Deploying healthcare IT uses. So this digs into, we talked a little bit in one of the earlier modules, and earlier in today's discussion, utilizing the practice management system to run data on CPT codes and reimbursements, which on the private practice side are the allowables, that's your cash in the door. If anyone wonders why it's hard for price transparency to work in healthcare, and I wrote an article about this when this first came out, because the federal government wanted to ensure price transparency to help consumer shop. And they said everyone needed to release their charges. Well, anyone in healthcare understands that charges, and you now know, that charges in healthcare delivery have no bearing on, almost no bearing on what your reimbursements will be. So let's look at these five new patient visit codes, 201 through 205. And let's look at these insurance companies, there are five of them. And you can see how this can get complicated, because not only do you have, let's say insurance company one, but insurance company one might have four different products. They might have a PPO model, a managed care, some high deductible something. So you can see how this gets really, really complicated, not only to negotiate contracts, but also to, if you're gonna go down some route of quote unquote price transparency, you have to know a lot of stuff to be able to get to price transparency. So in any event, here's where the data analytics come into play. I have all my, because I'm really good at this, I got all my insurance companies one through five, and I know what they pay me for each of these services. I can load those into my system, which when I go to negotiate down the road, I can look at insurance company, let's say one, and say, you know what, I don't do a lot of business with them, and they don't pay me very well, frankly, so I'm just not gonna negotiate. Or I'm gonna make such an absurd offer that they're gonna land well over these numbers, and my revenues are gonna go up even doing the same amount of work. So you can see how the other modules and other pieces, how the ecosystem has interplayed where these data points matter, because if you go and settle on a reimbursement rate for CPTs, and you have no idea what your patient volumes are, et cetera, et cetera, and granted, those aren't static numbers, because patients come and go into insurance companies, but it gives you a sense of where you are relative to, A, where you wanna be, and, well, actually, A. So in any event, using those data points, and there will be some give get on this, right? Maybe the insurance company's gonna pay me, like insurance company two, they're gonna pay me $130 for level five, and let's say they're only gonna pay me 25 for level one. Well, that's fine, I don't do a lot of level ones, but I do a lot of three, fours, and fives. So you can see how this works in both understanding and building out budgets, but also being able to negotiate with clinicians. And as I said, I believe I said this in the RevCycle portion module, there are a lot of medical clinics that don't know what their allowables are. And many that even know what their allowables are, they don't negotiate on an annual basis their contracts. And those contracts have, a lot of times have evergreen clauses. So they will just roll and roll and roll, and if they're tied into Medicare's allowables, when Medicare rates drop, so too do your contract allowables. So just some stuff to keep in mind, it's a lot of stuff, but I think the important part is to understand, and I hope I'm painting a clear enough picture about how all of these system pieces work together. And again, it makes the argument for my ecosystem diagram. So EMRs, you now have the opportunity with EMRs, and you don't need someone in a CHF clinic who's managing 800 charts and patients, because you can now do it via the EMR if you set it up the right way. So in my cardiac clinic 100 years ago, we use the EMR to manage congestive heart failure, and we had a clinic run by a nurse practitioner run by a nurse practitioner that we called the heart function clinic. And she managed all of the stuff, which really, that kind of stuff, theoretically is maybe not population health, but it certainly is a population of folks with a disease state that are being managed. And she had set criteria that things that got outside her scope of care, or any particular outliers were punted up to the physician who was our congestive heart failure specialist. But you could see how the EMRs theoretically will make that data and those analytics much, much easier to both deploy and utilize, whether it's population health or a disease state, or someone with diabetes or what have you. You can look at the data points, and you can do this on your own. These are things that, we talked about the measuring and metrics in one of the earlier modules. This isn't static, and certainly you can craft your own ID or craft your own data points by which to manage certain elements of a thing. And then we also talked about building out scorecards. So one of the things I did, the American College of Cardiology had three metrics. I think I'm gonna get these right. This was a long time ago. But the first thing I did is I built these into the system with my IT guys so that we could use those measures to make an argument that my guys were delivering good quality of care, at least based on those measures. So let's see. One of them was use of beta blockers post-MI. And I forget what the rate was or what the percentage was. And then I think, oh golly, I forget what the other two were. But I was able to put those in very simply. They are cumbersome so that we could manage and show and hopefully make a quality argument to the insurance companies why we were better, lower cost and we were managing in our specialties prescribed way. Now, when I pitched that to one of the insurance companies, they said, thank you, but we can't carve that out because we don't have the capability to do that with our IT system. So it is what it is. Fast forward 22 years and here we are. And now there's probably a little more play in that. Point of care decision-making tools. Again, I go back to cardiology. We put into, so diagnostics important in cardiology care and we had nuclear cameras and we had ultrasound machines. So what we did is I had one of my new guys look at an ASNIC article. That's a subgroup in cardiology, American Society of Nuclear Cardiology. And I asked him to grab the most recent article and pull out quantifiable metrics that we could use to then manage the care. And what this did was when a patient came in, it would look at, the EMR would look at, quote, unquote, read their chart before they got there for these, let's call it five elements. And if they had those five elements, a green light would pop up that would suggest at the point of care, it would suggest, I forget what the nomenclature was, but like new positive or whatever. And so then the clinician has that decision-making tool, understands that that suggestion was based on ASNIC criteria. And so maybe they need to dig into that a little bit more to understand, do we need to do this today? And if you take that and it doesn't remove decision-making, I think in my mind, it empowers it. Because then the clinician can say, you know what? Yeah, I get that. But where we are right now with all of these other pieces, everything's going okay. And so we're gonna maybe pass on this and do it at the next recheck or what have you. But again, the point of that is not the minutia of what I did back when I was a kid. The idea behind this is to show how these point of care tools can be out there. And many of them can be built in-house, quite honestly. You just have to be careful of butting heads with the logic and things that go on underneath the surface of the EMRs and the practice management systems. So you've seen this before if you've gone through the revenue cycle module. We talked about quality, rev cycle, provider production, overhead. These are IT components that are driven from your day-to-day work. I'm not going to get into too much detail on what this data tells us because we covered it very, I think very clearly in the prior module. But it is to say, and just to reiterate, so this stands on, this module can stand on its own. These data elements would be pulled from our practice management system. And again, theoretically, you can build out these benchmarks so your system puts these data elements in there and it automatically tells you without you having to pull out Excel spreadsheets, hey, we're better, i.e., if we look at our days outstanding, we got better versus last year and we're okay. But what if we were better, but we were over 28? Maybe that turns yellow because we need investigative work to happen. This would give your practice manager or your revenue cycle manager a quick and dirty look at those things that are going well and those things that are not going well. And it'll keep them from having to mash together 85 different Excel spreadsheets to get this done. This is a, really a metric, maybe doesn't belong here per se, but it gives you an understanding of the insurance companies and then what the percentage of the Medicare allowable is. And you can look at those things and aggregate again with your healthcare IT, all of the data and elements to understand which payer pays you what percentage of Medicare and then you can do the analysis. Do we wanna play hardball with them? Do we wanna walk away with them? What does that look like? And we did cover the, some of the quote unquote value to understanding your percentage of Medicare and what that means to the clinics. Production, other metrics, KPIs and benchmarking. Everything that we talked about beforehand in the other, in physician productivity in module one when we contemplated where you go, we looked a little bit at, excuse me, what your employment looked like. We did talk a little bit about the P&L, but here we're gonna get into use of healthcare IT in my compensation. And so when I look at this, I've got four physicians, excuse me, I put MD in there, my apologies, it's meant to be all physicians. The work RVUs there, Dr. One makes $32 an RVU, Dr. Two makes $22 an RVU, Dr. Three makes 42 and Dr. Four makes 55 for whatever reason. So you can see on the right hand side, there are their work RVUs that my IT system kicked out for me. And then there's the compensation they're making based on those RVUs. So it looks like I'm paying 32 times 4,500 RVUs and Dr. One produced $325,000. And so we're collecting $72.22 per work RVU. So you can see what this data tells us. We've got good margin on what we're paying versus what we're collecting. If you get down to Dr. Three, it's a different story down there. We are upside down on what we're paying Dr. Three. So the moral to that story as well, maybe we need Dr. Three because he or she provide some specialty nuance that we need to understand or we need it so that we get referrals. So maybe we're in the practice subsidizing Dr. Three, but if that goes on for a long time, we really need to understand, is this in our best interest? So overhead, we've covered this in several modules at length, but again, the healthcare IT, your practice management system should kick these pieces out to you so that you can get them fairly quickly. You don't have to wait three weeks after the month closes. So we're closed on the 31st and I have to wait till mid to late of the next month to get my data that we'll never do because I can't make good quality decisions. That needs to be timely. Some of this may be coming from another system or your accountant, but your accountant needs to be tied into this. I don't know if I'd advocate having your accountant like a link, a system that is integrated with this, or if they go in and do the work on your accounting platform, if that's QuickBooks or Quicken or Sage Intact or something like that. So let's look at it from a marketing perspective and I won't get lost in the weeds on this, but again, this is basically how you can use some of the data to market your new modality. We're just going to go through this very quickly. I won't belabor it. And again, you will have this access to the slides to alter these as you see fit or to go through the data as you see fit. In any event, we want to get a new laser for something. The other expenses over the life of the laser, including the marketing budgets, $25,000. So it's going to cost us $25,000. We're going to generate $250 per procedure is what we think. And so we're going to break even 500 procedures at 250 and we have a thousand procedure slots. So what we've done is we're going to look at, and I didn't even do the analytics for, could we make this work? Because again, we have to go back and understand the diagnosis codes and the CPT codes and who we have in our patient database. And maybe there's a demographic piece like people over 50, people over 60, people with MET, whatever that may be. We have to understand what our potential internal market could look like to see if these numbers work. And then we can think about externally marketing it. So we're going to market it here, and we're gonna buy these ad cycles. And if you're doing any advertising within your clinic, which we haven't really spoken to, I didn't think that external marketing necessarily needed its own module with regard to Practice Management 101, but here you're gonna get a crash course. Radio, TV, print ads, word of mouth. I will tell you that historically, and this is anecdotal, but I think it still holds true from the days when I used to do marketing for my clinics, radio ads, fairly expensive, depending on the market and the reach. TV ads, very expensive. Print ads, average. And then word of mouth is priceless, and it goes a long way. So what we've done here is we've done ad cycle one, and you can see in ad cycle two, we switched what we did because we were getting better play, it looks like, on print and on radio. So we moved our buy and our dollars to these areas. We did no TV because we got zero hits. So here you see, cycle one, we spent $1,600, 500,100, nothing in word of mouth. And then in cycle two, we spent the same amount, but 500, and you're gonna have to free it because of the math. I'm not sure how we bought 500 radio ads, maybe we got a discount at the same rate, but we did spend a lot more in print. And then we acquired in cycle one, 94 patients. And so what we can do is we can find out on our spend, we spent 50 bucks per acquisition. We got no one in TV, so we spent $1,000 and we got no acquisition, and then $17 of print ad for acquisition. So the bottom line to this, aside from a couple of mathematical issues, but the bottom line is you can use the data to understand how to grow a service line and then market it internally and externally. And this acquisition piece is really predicated on staff, on a good plan and staff understanding how to value those pieces and to track them so that you have good analytics and good math behind it, you can make good decisions. Value-based care. Again, this is driven a little bit of a mixed bag with your practice management system and your EMR, but let's say in a orthopedic group, I'm gonna go for a value-based proposition. And for me, basically value-based care means you are delivering care that is quote unquote high quality, which I can't dictate because I'm not a clinician, but you deliver it at a price that delivers value, right? And with some sort of maybe a promise or what have you. So manage quality and cost. Let's say in our example, we're doing a total knee. You assess the cost of that total knee, all the inputs, variable and fixed. You assess what the contracted price might be, and then you build in the quality measures so you can assure the payers you're delivering a value-based care product. So for instance, and again, absurd numbers, but I'm just painting you a picture. For me to do a total knee, it's gonna take $3.75 of a staff worker's time to get that patient prepped and whatever. Then the clinic flow workup is $4.38. Now, I'm not paying these people five bucks an hour, granted, but what I am doing is I understand based on my workflow and how efficient I am in optimizing my care that it takes a fraction of my front desk person's time because I have all these procedures, policies, everything else set up, takes them a fraction of an hour, which I figured out with salary benefits, it costs me $3.75 to do. Likewise with my MA workup, maybe it's an RN and an MA, but I figured out that that costs me $4.38 per total knee. My physician time, my doc is so efficient that he does this knee in whatever the case may be. I forget what the math was behind this that I came up with, but it's $250. And then the other indirects, we'll call them whatever, total $330.24 per total knee. I can go to Blue Cross Blue Shield or someone else. I'll go to insurance company number one and they're gonna pay me $10,000 because, and maybe they won't pay that, but this example is they're gonna pay 10,000 because they know I'm delivering quality care and all of these things individually from other payers are setting expenses higher and higher for Blue Cross Blue Shield. So it might cost them 15,000 per knee in reimbursements. So you're giving them a value argument and they're saving money. Likewise, if you take this to an employer who has their own insurance, like a self-directed healthcare plan, they're gonna look for savings. And if they're in a physical space, maybe a warehouse or someplace where there are some physical injury prospects, they would love this kind of arrangement because it helps them to contract directly. It helps them to manage their care and it takes the risk out of the care delivery and really the variability on what those costs are. So anyway, not exact science. These numbers are absurd. I'm trying to paint you a picture of the data elements that get behind a quote unquote value-based care delivery mechanism. And then issues, this came from a healthcare issues. This came from ESG, cybersecurity. This is a 2022. So this past fall issued, I think this came from a presentation and I do not know ESG. So I'm giving them full credit and attribution. Protected connectivity, we talked about. You better not be on your network at Starbucks unless you're using a VPN. Ransomware, we alluded to in an earlier module where a hacker will get in and I'm sure you've probably read about this in either some national newspaper or a healthcare-related newspaper or a throwaway where health systems have had their whole IT infrastructure locked down in the demand for Bitcoin or some other currency before records could be unlocked. Back in the day, we had a fallback where we could get to our charts or at least print off. We had a fail safe where we printed off things ahead of time so that if the system went down, we could at least have paper charts for the next day's visits. Not very practical, but that was what we felt we had to do in the early 2000s. And then HIPAA violations vis-a-vis healthcare IT. If you've got an open network and people get in it, you're at great financial risk for a HIPAA violation and dollars do flow out of your pocket for HIPAA violations. Blockchain and artificial intelligence, machine learning being a sub to artificial intelligence. I see the value in both of those in the healthcare space, specifically in care delivery. I don't know that I'm sold on those yet. I've written articles about AI and blockchain and frankly, artificial intelligence for the computer to quote unquote, learn what's going on, you have to have a solid foundation. So think about a pyramid where obviously you've got a nice robust framework on which to build the remainder of the pyramid and it's structurally sound. Just think of that relative to AI. We have to build out the tools and the inputs on the ground floor to ensure that the computer learns what's going on and kicks out actionable items that will benefit care. If that's not the case, the problem is you're going to have an inverted pyramid and obviously just think of that structurally, it's silly and it makes no sense. So garbage in, garbage out is my caution on AI. Blockchain essentially and this is going to not really do justice for what blockchain is but think of it this way. It is one data set, maybe one Excel spreadsheet that is accessed by multiple different constituents and so if let's say hospital system one, let's say hospital system has 10 hospitals in its network and they have one repository that keeps track of, I don't know, let's say meds for instance. When hospital one in that network pulls a med out of the storage area, everyone is updated real time of that transaction. So we had 10, hospital one pulled out a widget, we now have nine widgets, everyone knows that. That's the beauty of blockchain but blockchain reliant upon a single source of accepted data that people access and that gets updated in real time. And with multiple different data inputs, blockchain isn't going to fix healthcare writ large. Likewise, AI isn't going to treat patients next week and there have been massive failures in the AI space wanting to do too much across the board. I can see more application in AI candidly in a very limited delivery modality. Connectivity and storage, I am not the storage guy but there's cloud-based computing now which saves on cost. When I was a kid, we bought all the hardware which is insanely expensive and then you're updating hardware and software which is expensive. There is an argument may be made for software as a service, SaaS or cloud-based computing. We deployed a Citrix thin client network when I installed my EMR. So that basically meant that through the thin client network I can work from my home 35 miles away on the server in the office. So those things have changed. Candidly, I have not kept up with them. I'm just trying to give you a sense of some of those different avenues and bolt-ons and things of that nature. Issues, workarounds. So clinicians want to see patients, they don't want to be hampered. They want EMRs to have the functionality and utilization like a paper chart in terms of speed. And so what happens is if you have a bad install of your EMR you're going to create pain and chaos and ugliness for all the clinicians and we don't want that. And what a lot of entrepreneurial clinicians will then do is they will build out a workaround to get around the issue and that creates problems. I'll give you an example. I had a rural clinic, the CEO told me that one of the physicians was not productive. And I said, well, okay, let's understand why first. Have we removed all the systemic impediments, i.e. the operational stuff to make him or her efficient? Well, they didn't really know that. I said, okay, before we have that sit down with the clinician, you'd be best advised to make sure that he or she can see patients efficiently. What we found is one of many things, the EMR was not functional for this physician. So what Dr. X was doing was printing off referrals and receiving referrals via PDF file or printing off labs and that was just awful. And the system could do those things but they never implemented those appropriately. And so Dr. X was like, you know what? I gotta do this, I'm just gonna do it. Well, it made his life miserable because he was working 12 hour days seeing 10 patients a day, which makes no sense. So it's those types of things. We as non-clinicians, people like me need to figure out how do we make clinicians lives easier? That should be our goal. And by the way, that doesn't mean make it easier so you can see five patients a day. It means make it so if you're seeing 25 to 30 patients a day it feels like five patients a day and that you're getting out of the office or out of the hospital at a reasonable time. Schedule blocks and utilization. I had a rural clinic in the far West of the United States and they had doctors blocking their schedules for a full hour. That's not really a healthcare IT issue but it is a care delivery issue and it makes no sense. But they had to do it because the documentation process within that EMR was cumbersome and kind of a nightmare. So you can see again that it just ruined efficiency for the clinic. The cost, EMRs, anything IT is gonna be fairly expensive but what you don't wanna do is shortchange the purchase some of the bells and whistles that make sense in the implementation because a lot of times the ROI, the return on investment for an IT thing is gonna be hard to really nail down. But if you should pay $100,000 for an EMR PM system and you say, well, you know what? I just needed to do this. I'm gonna pay $100. You're gonna pay a hundred thousand fold or you're gonna pay multiple times a hundred thousand just to repair that and get that working. So the caution, the efficient caution is don't cut off your nose to spite your face. When there is an EMR deployed, people should not have the option to use it or not use it. That creates chaos and havoc in the operational space for the non-clinicians, likewise for the clinicians and your lay staff, your APPs too. You want everyone to embrace and utilize the practice management system and the EMR. But two, you really should have physician input on the construct or the rollout of the EMR and practice management system. Not so physicians have the final say, but so they have input about things that are gonna impact them in the delivery of care. It only makes sense. And I've talked about this when we talked about operations. Physicians need to have a seat at the table to talk about the things or understand the things that are gonna impact their lives practically and or pragmatically speaking in care delivery. I've said this before, in my estimation, implementation of an IT system, even if it goes quote unquote 100% perfectly, it's only about 80% because these things have a lot of moving parts. They are never, ever perfect. And I'll give you an example. My first install to my best way of thinking was 100% good. However, as we loaded our payer contracts into the practice management system, the gentleman from the practice management, the company that sold us the EMR, he transposed two numbers in what was probably a 12 or 14 number numbering system in the contract. And that transposing those two numbers made my charges back up multimillion dollars for about two months until we found out what was going on and fixed it with one of my largest payers. So here I am then, I don't have that revenue flowing through got to make that change, then rebuild all that, then make sure we get paid for all that. So you can see how this works. I won't belabor this slide because I feel as though I'm getting a little long today, but you all have seen this ad nauseum. And again, I would suggest to you, this stands true. This shows the interrelationship of the healthcare IT, the rev cycle, the care delivery, et cetera, et cetera. It is the ecosystem. So that is my presentation for today with regard to module six, healthcare IT. I appreciate again, you spending time with me. I hope you got some value out of today's discussion. One of the things that we didn't discuss is how these interrelated piece, well, we didn't discuss at length some of the external interrelated pieces and how data gets dumped from PAC systems and things like that, imaging systems. And my apologies on that, but the macro logic and discussion that we talked about really does contend with those if you think about them on the whole. So as with modules one through five, we are aggregating your questions. If you have questions on this or any of the preceding modules or module seven when that comes out, please submit them to physicianservicesatosteopathic.org. If you can, please submit those by May 10th. May 10th, we are going to have a live Webex where we will answer those questions. We're going to, the hope is to build out a presentation module akin to these so that once we're done, we can release the recorded on-demand presentation so that you can go through, listen to the questions and understand. But having questions submitted ahead of time gives us a lot of time to noodle questions. If I have to dig deeper on some items that I'm not a subject matter expert, I can query a couple of my folks for expert opinions to understand and better answer those questions. In any event, that Webex will be seven o'clock Eastern time. The connectivity information will come from the fine folks at AOA a little bit later. So if you cannot make it at 4 p.m. Pacific time, as I noted, this will be recorded. It will be ready for on-demand presentation at a later date and time. So without further ado, again, my thanks for your time. Look forward to, or I hope that you all will join me not only for preceding presentations and modules, but also for module seven and then module eight on the 23rd. Thank you so much for your time. I appreciate it very much.

healthcare IT

electronic medical records

practice management systems

data analytics

EMR implementation

security

AI in healthcare

blockchain

HIPAA violations