In this episode, we are joined by Michael Duke, Author of The McPherson Principle, to give us some actionable advice on topics related to revenue cycle management, employee performance monitoring, and healthcare finance.Learn how to listen to The Hospital Finance Podcast® on your mobile device.
Highlights of this episode include:
- The McPherson Principle
- Automated revenue cycle
- What is the process effectiveness ratio
- The operational efficiency ratio
- The employee performance ratio
- The keys to revenue cycle performance improvement
Mike Passanante: Hi, this is Mike Passanante and welcome back to the award-winning Hospital Finance podcast. Today, I’m joined by Michael Duke, author of the McPherson Principle. Michael has over 30 years of diverse experience and a record of accomplishment in leading people, programs, improving operational outcomes, and developing best management practices within the healthcare industry. He’s led several successful engagements that demonstrated an ability to develop and execute executive level strategies. He’s proven expertise in the areas of operations management, corporate performance management, and revenue cycle management. Michael is going to talk to us about his new book and offer some actionable advice on topics related to revenue cycle management, employee performance monitoring, and healthcare finance. Michael, welcome to the show.
Michael Duke: Thank you. Glad to be here.
Mike: So why don’t you start off by telling us a little bit about yourself and give us an overview of what the McPherson principle is all about?
Michael: Okay. Sure. So a little bit about myself. I am now rounding after my 30th year in healthcare. That’s the only industry I’ve ever known and have played in. But I have sat in a lot of the management seats. And by that, I mean I’ve run IT departments, I’ve run revenue cycle areas, and I’ve run operationally for organizations, but I’ve also provided a lot of guidance on those as well. So through the course of my career, I’ve had a variety of consulting roles and guiding clients on things like technology implementations, analytic deployment, revenue cycle improvement initiatives. So on the finance side, a lot of experience, and on the operations side, pretty significant as well. But, yeah, pretty excited on some of the things that I’ve been able to do and where I see the industry going. So that’s fun.
The McPherson principle is really taking some of the lessons I’ve learned over the course of my career. I’ve had some great leaders that I’ve been able to follow and learn from, and I wanted to encapsulate some of that, but then, also, kind of push it forward. Our industry tends to lag, as anybody listening to this probably knows, from an innovation standpoint, and things are coming at us pretty fast nowadays with a lot of the automation through robotic process tools. We’ve got some really interesting analytics through some of the augmented analytic tools that are coming at us. And I wanted to take some of that plus some discussion around workflow. When we do need a human to interact with things, what does that really mean and how can we enhance that? So trying to take a look at the technology, but also some of the best practices on how things should be done and put that in a book that was more of a story instead of straight up educational literature. So that was the genesis, and been thinking about it for a few years. And of course, with the opportunity to work from home during the COVID kind of break, I thought it was a great time to finally put pen to paper.
Mike: Yeah. It’s an interesting format you came up with. And as we talked a little bit before we began recording the podcast, you mentioned this idea that everybody kind of measures AR days and some of the typical benchmarks that we have in revenue cycle. But there are some other maybe best practices we can bring in to this from other sectors and really get in tune with this automated revenue cycle that we’ve been talking about.
Michael: Yeah. And that was a good push forward as well. So going back, gosh, maybe 20 years or more now, I was exposed to a book called The Goal by Eli Goldratt. And it’s a manufacturing environment, but it’s a fictional story of a plant manager going through the opportunity to evaluate how things are accomplished. And looking at it, you’re seeing what everybody else is seeing, but looking at it in a different way. And that book has always resonated with me from the concept of product throughput and how do we enhance not just throughput of, let’s say, a machine operated system, but also how do we improve employee and personnel throughput. So the human interaction with that. So that’s always been in the back of my mind. And the concept of the way that book was constructed, again, is more of a– it was educational, but also a storytelling exercise. And that made it easy to absorb some of the more critical concepts. So I wanted to do the same kind of format; to make it an easy read, but also pass along primarily the three concepts of process effectiveness, operational efficiencies, and employee performance. Because if anybody’s dealt with any consultant at any point in time, we talk constantly about people processing technology. So I wanted to kind of take those three and mold them into potentially new metrics that we can use as an industry to look at the same things we’ve been looking at forever, but understand them potentially in another way to drive performance.
Mike: And that’s a great segue into my next couple of questions, because I’d like to dig into those ratios and just put a little bit more meat on the bone there. So why don’t you talk to us about the process effectiveness ratio? What is that?
Michael: So process effectiveness is measuring how well things flow through the system. So an easy one that I think everyone would be able to digest is really around if I bring in a patient to a point of scheduling or I go to my physician’s office or whatever it might be, from that point of contact forward, how can I make that claim go through, for example? All of the things that go into making a claim and the submission without any hiccups at all. So no bill holds, no denials, no rejections, the things where a human being has to touch it. And if my process is 100% effective in the definitions that I used, it measures how well work is being performed, but it also measures how well technology is enabling that process. Combine all that together, and we really get a measurement that is around the– back to a little bit on the Goldratt theory, the throughput of work activities that have no error rate. And that’s what the process effectiveness ratio is really about, is the more we can keep that under manageable level, the less delays we have in cash performance, the less write-offs we have to denials, and the less costs we have in the internal workings from an employee standpoint, all three factors which impact our financial performance as an organization.
Mike: Okay. So sort of next in the sequence is the operational efficiency ratio. Why don’t you tell us about that?
Michael: Okay. So a nod back to the process effectiveness, that’s how well things go through the system. The operational efficiency ratio, the way I constructed it or why I constructed it, I guess, is really trying to understand the speed in which it goes through. So minimizing delays for charge entry, minimizing all the things that, of course, we want. This has no impact on the care given to the patient, but really all the administrative steps that are required. How do we measure how quickly those are performed? So that, again, it’s more about this is more related to the cash flow and the cost side that the faster I can process those things and the faster in which I can get the payments received. So on the cash velocity, the quicker I resolve those accounts, the quicker I have more cash in the bank, and those things. So the operational efficiency was around the speed of the activities or the process. The process effectiveness ratio, that we just talked about, is more around the quality kind of aspect of the work.
Mike: So rounding out that trio is the employee performance ratio.
Michael: Absolutely. And we keep trying to get to the point where we don’t need FTEs in rev cycle, and that’s just not going to happen. Now, can we minimize it? Absolutely. But when we do need a knowledge worker to perform a task, one, how do we elevate that task level so that it has a higher contribution to the organization as opposed to just pushing paperwork around? And then how do I elevate their performance so that they can do more and they do it in a much better fashion? So the employee performance ratio was constructed to try to understand a knowledge worker’s speed, so their productivity, and their effectiveness or their quality. I remember years ago when I was first being trained as a consultant, we would go through and audit 10 accounts or 20 accounts, or whatever it might be, for a particular job function and try to score those. And of course, that’s evolved a little bit with some of the tools available, but not a lot. So the EPR was a way for me to try to say, “You know what? I want to be able to look at 100% of someone’s work from a productivity and equality standpoint. How do we do that?” So the EPR was constructed to really put together– that’s why it’s performance, not productivity. It’s really to understand how much they do and how well they do it.
Mike: Excellent. So if we take all of that information and think about where we’re at in revenue cycle today, what do you think are some of the keys to revenue cycle performance improvement?
Michael: The biggest and– well, not the biggest maybe, but it’s really leveraging some of the innovative technologies that are out there. So I’ll step back a couple of years. We’ve had claims data [inaudible] through EDI transactions and those things. But we’ve really got to have some automation internally throughout the process, as well as externally. So automation is a key innovation. One of the things that I’ve been exploring with for the last, I don’t know, 18, 24 months is really around taking analytics and applying that to the automation functions, so if I can start using machine learning to determine when Mike Duke performs a task that is successful, whatever it might be. So I fix a claim, I rebill it, or whatever the steps might be. Well, how can I then learn from that analytically and then apply that to an automation component so that Mike Duke doesn’t have to do that task any longer?
So those are some of the things that I think are slightly being touched on now. You read a lot about it around the artificial intelligence and those things and machine learning, but really, at least my client base, I don’t see them applying that as much as they really could and push the envelope. So using that innovation. But then, the flipside of that is I really am adamant around the augmented analytics piece. So we need to leverage proper visualization techniques. There are methods in which the human brain consumes information. And unfortunately for most analytic tools, it’s not in large table sets, it’s not in rows and columns. It’s in pictures.
That’s why when 2,000 years ago, 200,000 years ago, whatever it might be, we were drawing on caves. And we weren’t drawing numbers; we were drawing animals and pictures of what happened. And the human brain absorbs more information through a picture than any other way. So can we construct revenue cycling analytics that allow us to see things very quickly and make decisions very quickly? So that’s another big piece of it, along with the machine learning and automation that I just feel like have to be front and center over the next couple of years if we’re going to make any major strides.
Mike: Absolutely. When you think about operational performance, Michael, what are some techniques that providers can use to improve operational performance?
Michael: One of the things– and this is not a– I’m not trying to bust on the large EMRs that are out there now, but some of the things that we fail, I think as an industry, is the definition of workflow. Again, where most of the hang ups come from is either through human error, which is natural. We make mistakes every day. That’s why we’re human. But when I do need to have someone involved in work, is it the most valuable thing they can do? And that’s one of the things I talk about in the book as well, is the next most valuable activity. I can list you year after year after year of examples where people do the easiest thing– nobody goes to work trying to mess up or not provide value, but there’s also days where you’re just having a rough day, and so you’ll do the next easiest task. And that’s not always the best thing for the organization.
So building toolsets that allow technology driven by management business rules that assign the next most valuable activity for someone, I think is a concept that can be deployed today and advantages can clearly be made. So setting up a workflow situation instead of work queue situations, which is what, unfortunately, we have now. And I may get a lot of pushback on that, but I have clients that have every tool, every EMR out there, and they’ll have 20,000 work queues. That’s not a workflow system. So understanding the difference between true workflow, which takes data, which takes human input, and is updated constantly to adjust on where things should go and who should be working on them as compared to work queues, I think is something that should be explored by almost every organization that has revenue cycle function.
Mike: Very interesting perspective there, Michael. Last question for you. Healthcare organizations generally are– they do everything they can to improve their financial performance, it seems. There’s all kinds of initiatives and technology and just lots of mindshare put behind that. How likely is it that most healthcare organizations can improve financial performance realistically going forward using some of these new techniques?
Michael: It’s tough because everybody thinks they’ve already done all the major rev cycle improvement that they can make, and maybe there’s a tweak here, maybe there’s tweak there. Or I talk to a lot of clients and they, “Oh, we just fixed that. So we’re going to wait 18 months to see the results,” which is just mind boggling to me because I should be able to tell you in about three weeks whether you’ve made the right improvements or at least on the right track. But I, personally, believe that almost every organization still has pretty large improvements. And the reason being why I think that is some of the points I made earlier. I don’t think we are looking at the business any differently, for the most part, than we’ve looked at it for the last 20 years. I don’t think we’re really pushing the envelope on innovation to make dramatic improvements. And I don’t think– and, again, this is no criticism.
It’s where you’re from and where you’ve grown and what you’ve seen. There’s a lot of people in healthcare management that that’s what they’ve seen and they haven’t explored other solutions or taken a step outside of the healthcare box. I mentioned that I was– I’ll get back to this, but a little rabbit hole here. But I mentioned I’ve been in healthcare for 30 years, but it’s been a tremendous amount of time in manufacturing with friends of mine that I’ve gone to school with. And [inaudible] I just want to see it, talk to me about your technologies, talk about how you monitor process. And one of the tools that I’ve built over the last couple of years around analytics was because I was talking to a great friend of mine. He’s actually one of the dedications in the book. He and I were having lunch. And he used to build the large elevator silos for skyscrapers. And I said, “How do you understand when things are going to break down?”
And he said, “We know when parts are going to fail before they fail.” I said, “Okay. Talk to me about that, because I want to know when revenue cycle processes are going to break down before they become problematic and we lose money.” So he talked about all of these control failure points that they measure every time an elevator goes up and down. And I’ve been in a million elevators, I never would have thought of all the sensors they have on these things. And I said, “If we could do that with rev cycle, man, we’d be so much farther ahead of the game.” So coming back to your question now, I believe the management in healthcare is– a lot of times you’re promoting from within or you might go from organization to organization, but you’re seeing the same things you’ve always seen. And that’s one of the things that I would challenge healthcare leaders, particularly around rev cycle, is step out a little bit and go see some other stuff at other industries and how they’re solving problems around process and technology and employee performance. And there’ll be some things there that if we apply the principles, not exactly, but if we apply those principles, there’s still large gains to be made operationally and financially for healthcare organizations.
Mike: Yeah. Really good advice. I think we see in healthcare that it feels like we’re always playing catch up to some extent. You see that now on the patient experience side, for instance, and people wanting to interact through apps and other kinds of technology that in the consumer world is sort of taken for granted. Right?
Mike: Yeah. Yeah. It’s interesting. Well, a lot more to come in healthcare. Great advice today, Michael. If someone wanted to get a copy of your book or find out more about you, where can they go?
Michael: So there’s a couple of ways. The McPherson Principle is available on Amazon. So if you just search for, and again, it’s M-C-P-H-E-R-S-O-N Principle, it should come up. There’s also a mcphersonprinciple.com website that you can find it. And then really, those are the two good locations. You can contact me through either one of those. I’m also available at firstname.lastname@example.org. But, yeah. If anybody’s interested, I’d love to chat about it. It’s something I think about every day and I’m pretty excited about getting the book out.
Mike: Excellent. Well, much luck with it, and thanks for coming by the podcast today, Michael.
Michael: Okay. Thank you, Mike. Appreciate it.