Making Rounds: The Big Squeeze in Healthcare [Podcast]

Labor woes, an EBIDTA crisis, a clinical tsunami, and disintermediation continue to put considerable pressure on healthcare systems; the Big Squeeze has only tightened its grip. As organizations look to move forward in a changed ecosystem, it’s critical to leverage people, data, and technology in new ways to freeze the squeeze and lean into this new era of care delivery.

In this episode of In Network’s podcast feature Making Rounds, Head of Thought Leadership Dr. Jerome Pagani chats with Digital Health Practice Leader Kevin Erdal and Managed Services Practice Leader Paul Slaughter to discuss the many challenges facing healthcare systems, including risks from new entrants, as well as how healthcare systems can do more with less, and ways in which technology can be used to identify and ameliorate these growing issues.


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Show notes:

[01:38] The factors driving the Big Squeeze and their effect

[03:17] Risks of new healthcare entrants

[05:16] How healthcare systems can do more with less

[14:06] How technology can identify and ameliorate challenges



Dr. Jerome Pagani: Kevin, Paul, thanks so much for joining me today. Can you take just a second to introduce yourself?

Kevin Erdal: Sure. I’m Kevin Erdal, a practice lead for digital health here at Nordic.

Paul Slaughter: Paul Slaughter. I'm the practice lead for managed services here at Nordic.

Dr. Jerome Pagani: Thank you both for joining. So, we're going to talk a little bit today about the Big Squeeze, and what we're really talking about are the plethora of challenges that are putting enormous pressures on healthcare systems. So, Kevin, Paul. What are some of the factors that are driving the squeeze, and what effect are they having on health systems today?

Paul Slaughter: Yeah, so I think healthcare is seeing skyrocketing costs across the board. I think we see global inflation. We see geographic inflation, geopolitical instability, you know, all kinds of different things that are affecting financial performance of health systems and not in a positive way. You know, we're seeing a lot of expenses that are outpacing revenues. It's impacting those health systems’ ability to staff appropriately for clinical care and operational improvements across the board is suffering. What we're starting to see now on top of that is we've got Long COVID, post-COVID sequalae all escalating the chronic care burden to these institutions. And so, I think what we really need to think about is what are those effects on revenue, staffing, capacity, and then what can we do from a technology perspective to address it?

Kevin Erdal: And even from a technology perspective, right? We're expecting things differently in today's world as patients. So our patients are expecting to interact with their clinicians a little bit differently than they did four or five, ten years ago, where we now need to have applications on our mobile devices so that we can interact with not only their clinicians, but sometimes the collective care team, and not just for an individual as a patient, but in some cases as their families. So now we have a different level of engineer, we have a different level of technical debt, all of those are contributing to the Big Squeeze as we think of it.

Dr. Jerome Pagani: Yeah, and you touched on kind of a critical point there, which is that patients are beginning to have experiences in other sectors that are leading them to have expectations of what they're going to encounter in healthcare. Is there a risk there for other players to come in and begin to develop their own health services?

Kevin Erdal: Yeah, a risk and an opportunity, right? So, because there is an opportunity for us right now within healthcare to learn from others, I think we can take advantage of that. So, I can now pull up my phone and look at my Uber app and get a ride to anywhere I maybe need to go within the Madison area, for example. If I need to book a flight to go someplace a little bit further, I can do that from the same device and have relatively the same kinds of experiences. So as patients and as family members, we now expect that out of our healthcare systems as well. I need care. I need to go find that within the region that I'm at right now. And I might want to find care for maybe my child who needs a well-child visit. I want to be able to help her, support her, for the same device that I'm booking my flight from.

Dr. Jerome Pagani: Some of those retail and tech players, for example, really have experience doing that end-to-end customer journey really well. What we've seen is that some of those players are making investments on the healthcare side and bringing that set of experience capabilities to bear as well.

Kevin Erdal: Yeah, Amazon, Walgreens, CVS, they've all done this pretty well for a period of time, broadly speaking. Right? And now we're getting a little bit closer to healthcare as well. So, we just need to make sure that we're on pace with the changing ecosystem around us from a technology perspective.

Dr. Jerome Pagani: And that's the opportunity for more traditional healthcare providers, is they understand the care space really well and their opportunities to either partner or to build in-house or to bring in a vendor to build out some of that experience piece.

Paul Slaughter: They risk significant disintermediation if they don't do that, if they don't invest in those areas. They will get cut out of the care continuum and revenue stream.

Dr. Jerome Pagani: Yeah, and I think we're starting to see that as care becomes more decentralized, there are more players. It's delivered closer to where health consumers are, and there are opportunities then for fragmentation of care. And so, what we really need to be thinking about is that ecosystem perspective, as you mentioned.

Paul Slaughter: That's right.

Dr. Jerome Pagani: So, a lot of those factors that we're calling the Big Squeeze are resulting in health systems having to do at least as much, if not more, but with fewer resources, both on the financial end, on the people end, and thinking about how to use technology in smarter ways. Can we talk a little bit about that?

Kevin Erdal: Yeah, so I can maybe start off, Paul, and I know you can help add in from a staffing component of it as well, but when we think of where we can leverage technology and then how to leverage that technology, it becomes critically important to consider the changes in the impact not only to the workflow but also to the overall patient experience. So just a couple use cases or a thought or two on this particular topic, right? So, look at robotic process automation is one example where back-office type activity, maybe from a revenue cycle perspective, and helping with things like claims denials, can be very helpful. We don't have to have individual staff members looking at a multitude of different claims and trying to reprocess, and that might be an area to consider in that back office, not so much patient-facing, to bring in some net new tech. The other piece of the puzzle is artificial intelligence, which is extremely exciting, and we all like to talk about it right now, but we have to make sure that we're doing it in a safe environment and that we're impacting workflows in a way that we intend. So, for that reason, we always want to bring the clinician into the mix as early as possible and start to understand where can we start to derive insights early and then inform the clinician to help make decisions instead of trying to do some processes without understanding the end-to-end impacts.

Dr. Jerome Pagani: Is that kind of the progression that we're seeing? So, we're seeing use cases for things like AI in particular, really working very strongly in the back office and establishing that safety and trust so that they can then be rolled forward into clinical operations as well. 

Kevin Erdal: Yeah, back in mid-office is where I would say we see the most of it, and then we start to see that creep its way forward into clinical care, which is extremely exciting and that's where we all want to be. But once we understand how to bring artificial intelligence into a particular health system, the safe place to start is farthest away from patient care as possible and then start to bring it closer to patient care and impact in a positive manner.

Dr. Jerome Pagani: So I think technology is great and is an enabler, and it absolutely needs to be part of the overall solution. I think we also can think about this in terms of how we actually can staff certain functions within healthcare organizations and how you can reduce burnout, reduce your attrition of staffing, as well as take some of those administrative tasks, the lower-end rote tasks that people have to do every day off their plate in a manner that allows them to focus on the more higher value strategic or at least critical to clinical care and the support of that clinical care via their EMR and other systems. I think there's an opportunity to augment staff to ensure we help those health systems basically retain the staff that they have and perform at the top of their license.

Dr. Jerome Pagani: So one of the things managed services has always done has been able to meet those sort of fluctuations in demand in a really timely and efficient way.

Paul Slaughter: Absolutely. I think managed services, one of the value adds there, is to smooth out the peaks and valleys as you think about delivery on a monthly, weekly, daily basis. We can definitely do that from a scale perspective that a hospital or health system just can't afford to staff to. So that's definitely one of the pieces that we would bring to the table.

Dr. Jerome Pagini: So in addition to that sort of people side of augmentation, I think what I'm hearing is there's also an opportunity to use some of the automation to combine those two, the people in the technology in a way that helps meet those fluctuating demands.

Paul Slaughter: Absolutely. And that's kind of where we take the concept that Kevin has brought and the concept that I brought together to say, you know, there is the right place to start. I think Kevin has nailed it. We start in the back office, we build the use cases, we build the RPA and AI tools to address the automation for the 80% standard business process that doesn't change. We let those resources focus on the higher value, more strategic aspects of their daily jobs. And then you start to bleed that into, okay, where can we now address that from a clinical decision support and clinical care perspective, and you start to build out those use cases. And I think you might move a little slower, but the value there is going to be tremendous because the burnout issues that you see in back office are greatly accentuated when you look at the front of the house from a clinical care perspective.

Kevin Erdal: Yeah. And I think if you just look at a couple of different examples, right, if we could leverage technology, whether it be RPA or AI in general, to derive some insights to prioritize the workqueue, for example, that's going to make somebody maybe from Paul's team or one of our client sites more efficient and increase job satisfaction overall, right? They're working on the problems that they took on as a clinician, if you will, or as a professional, to solve. And that helps bring some additional level of job fulfillment, if you will, or personal fulfillment, I should say.

Paul Slaughter: I think whatever we do, it's got to be a multipronged plan that then gets that kind of force multiplier of staff aug staffing from a managed services perspective plus technology, just makes a one plus one equals something well beyond two.

Dr. Jerome Pagani: And we've seen some of this already working inside the hospital system where we're using a combination of people and technology to do things like managed care by exception. And as health systems are thinking about their click-and-mortar strategy, this seems like an approach that can be taken outside of the hospital and into the broader health ecosystem.

Paul Slaughter: Absolutely. I mean, think about virtual care and all the capabilities there and the ability to see patients as they want to be seen in a different environment that doesn't require you to build a new clinic. It requires you to staff a technology solution that a patient can consume wherever they may be when they need care.

Kevin Erdal: Automating a bad process is a bad idea. We want to make sure that we consider the workflow enhancement component first.

Paul Slaughter: I completely disagree. I completely disagree. Who cares? Why would you? If I'm a health system. Okay. And you said, gee, Paul, your HR onboarding process takes 23 steps. We could do it in five. All I need is six weeks of a business analyst's time and disrupting my HR team to redo the business process and automate it. Versus, I typed the code for 23 steps. As a developer, and I never touch HR, and who cares that, when I get to the millionth line of code, then I go back and I look at how I can fix it. But if you're automating it, who cares? Don’t …

Kevin Erdal: Two things ...

Paul Slaughter: I want to sell that project, don't get me wrong.

Kevin Erdal: Yeah,

Paul Slaughter: Why would I ever, as a health system, spend money …

Kevin Erdal: You're talking about time and duration. I'm saying if you don't look at the workflow, you're not going to address inaccuracies.

Paul Slaughter: Okay, workflow, that part I get. Bad process is one thing, but needing to re-engineer a process before you automate it … if the process is not inherently broken, don't re-engineer it before you automate it. Just automate it.

Dr. Jerome Pagani: What's a bad process?

Kevin Erdal: A bad process?

Paul Slaughter: Don't say inefficient process because that's not true. If data collection is wrong, then that's wrong.

Kevin Erdal: A bad process is a process that could lead to inaccuracies. So, without analyzing the workflow in the process, you will not be able to articulate whether it's a good or a bad process.

Dr. Jerome Pagani: You get erroneous data rather than it being just broken.

Paul Slaughter: And I think you can evaluate the processes that you're looking at that are candidates for automation, and you can do a risk-based assessment of that, and say, three categories: the risk is minimal; this needs to be looked at; and this needs actual process redesign. I'm disagreeing with just the general statement.

Kevin Erdal: Sure.

Paul Slaughter: Because I think it's shades of gray, you have to think about, why would I automate … if my onboarding percentage for, to use that easy example, if my onboarding percentage based on the current business process is only wrong 1% of the time and it's just HR onboarding. Why would you care?

Dr. Jerome Pagani: So I'm hearing there are two approaches here. One of them is a top-down approach, and the other one is very much a bottom-up approach. So, is there some rubric for thinking about how you would tackle or divide and conquer?

Paul Slaughter: I think so. From a consulting perspective, I'm telling you you need to re-engineer all of your processes. But from a technology and from a realistic perspective, I'm telling you, your money's best spent on the higher risk data discrepancy areas than the rote administrative easy back-office tasks.

Kevin Erdal: And the reality is the only way you can understand what is going to be leading to an inaccuracy versus just a long, drawn-out process is to do that assessment that Paul hit on a minute ago. So, there isn't a silver bullet there necessarily, right? You really have to sit down, understand what the process is, understand what your risks are. And that's why we were talking about back office is a little bit safer place to start for some of these things versus more patient-facing, patient-forward kinds of processes.

Paul Slaughter: Yeah, I totally agree with that.

Dr. Jerome Pagani: One of the places where technology can have a big impact that we've only sort of touched on is ameliorating the conditions that health systems find themselves under in terms of financial and operational pressure. Kevin, can you speak to the ways in which technologies are helping identify some of those hotspot problems and how they're being addressed?

Kevin Erdal: Yeah, some of this goes back to utilizing data, right, to help inform what the organization is doing today versus what you can expect to come. So that's where we get into some of the predictive analytics as well. So, we want to make sure that we're understanding exactly what's happening within our current populations and understanding how those populations might change or evolve over time and then take that information and start to apply it to our resource plan that we have in play right now versus what we might need to change or maybe redirect, if you will, as we forge ahead into the future. So, it's really going back to some of the basics in terms of utilizing your data as an asset, starting to not only predict what's coming in front of you, but also understanding how you can care for some of the patients differently based off of what's happened across your organization and or what's happening outside in other organizations and starting to apply that to your individual health system.

Paul Slaughter: That's exactly right. It is care delivery for processes sake versus exception-based medicine, I think is the key way to think about it philosophically.

Dr. Jerome Pagani: And that benefits the patient as well, right? They're staying engaged with their health. There's sort of high touch, but not intrusive levels of care.

Paul Slaughter: Yeah, I think as we get this model right, I think the patient not only are the care delivery resources and staff going to feel like their time is better utilized, I think, again, coming in every month for a patient visit because it's your scheduled time versus seeing data come in via telemetry for virtual care devices informing you, hey, to two weeks from now we want to see you because we see this data presenting differently. I think that's the key is delivering care as it is needed, not as there is a schedule and time and process requires it.

Kevin Erdal: Yeah, a wise man once told me, “Make it easy for me to do the right thing.” That's Mr. Craig Joseph, who is our local CMO. And really what we can do with technology to help enable that is coming down to leveraging the information that has been derived, putting in front of the right decision maker, whether it's a clinician or a clinical operations persona, whatever the case may be. But make it simple, right? Make it something that is kind of part of your day-to-day routine, part of your business, and that way you can stay informed over time as well.

Paul Slaughter: I think Craig also talks about, you know, make sure that you can take the technology and process through that the last mile. So, make sure that whatever you do is easily effectuated at the very end of the process, which generally ends with a nurse, a physician, a clinician.

Dr. Jerome Pagani: We are writing a book together, actually. And one of our key points is to think about that sort of end state and the end user and work backwards from there.

Kevin Erdal: Yeah. And the backwards part, to add on that maybe one last piece is what is going to be an enabler. And that's where we're starting to see some of the cloud transformation to make sure that if we have to add net new technology, if we have to bring in net new data sets to start to inform, we have a scalable environment to accommodate that so that we don't have yet another barrier to make it easy to do the right thing.

Dr. Jerome Pagani: As we've talked to people about the book, one of the topics that has come up repeatedly is how often technology is put in place with a process that suits the technology and then the difficulties that creates for those giving and receiving care. And we can see, from the pandemic and even before, just that, there is this sort of feedforward loop where all of those little difficulties make giving care, in particular, harder, and that contributes to burnout, and that becomes a feedforward thing where we have fewer staff, and it's harder to retain, and the price of labor goes up. So, I think one of the things that we're talking about using technology for is to do things like make sure that we're using the data so that we know how to decrease the number of clicks a physician has to do, or use AI or ML to do things like automate scheduling or control throughput.

Paul Slighter: I think that's key too. And again, that's where most organizations don't have the staff to take the technology and evolve it and transform it and mature it. And that's where I think when you backfill some of that standard work with a managed services organization, that really does free up again those people to operate and go back, and your clinical informatics get to liaise with the clinicians and the care delivery teams and truly understand how to leverage the technology to its maximum benefit versus, you know, you implement the technology for technology’s sake and you never really get the true benefit.

Dr. Jerome Pagani: Yeah, I love that. So, it's not having that one-and-done mentality. There's that continuous improvement mentality, but you're bringing in the folks who are experts at doing that part so that your own people …

Paul Slaughter: Yeah.

Dr. Jerome Pagani: … can focus on the mission.

Paul Slaughter: I think ultimately your technology architecture becomes unwieldy if you don't. I think maximizing the technology allows you to actually do more with less technology via clinical care process, etc., then adding another tool for each boutique, nuanced thing that needs to be done in the organization.

Kevin Erdal: Yeah, 100%. Technology without an expert is just technology at the end of the day, you're not going to be helping anybody. So, bringing the folks that actually know how to care for the patients closer to the technology roadmap, if you will, and understanding what the use case is, the better. You're going to have a better long-term experience and not just a one-and-done kind of implementation saying, oh, we checked the box, we implemented a particular cloud-based platform, that's great. What problems are you solving, and are you thinking about the problems that are three to four years down the road as well? You'll never be able to articulate them in great detail, but you can start to understand, okay, how can this scalable platform support me long-term and near-term?

Paul Slaughter: And I think the only thing that I'll put on top of all of that is I think you've got to have the appropriate governance structure where you're bringing in your clinical informaticists as you're bringing in your clinicians, your physicians, your nurses to work and liaise with technologists to ensure you're getting the balance correct. I think that's key as well. You can have great technology, you can have great service augmentation and automation, but if you don't continue the dialog and keep it up and put effort into it from a governance perspective, I think your outcome is going to be limited at best.

Dr. Jerome Pagani: Kevin Paul, thanks for joining me today to talk a little bit about the big squeeze and some of the things that health systems can think about to ameliorate those problems.

Kevin Erdal: Happy to be here.

Paul Slaughter: Yep. Thank you so much for the time.

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