The Hospital Finance Podcast

Besler Holdings

If you’re concerned about revenue at your hospital, then The Hospital Finance podcast is your go-to source for information and insights that can help you protect and enhance the revenue your hospital has earned. From regulatory changes to revenue cycle optimization, readmissions to bundled payments, you’ll get important perspectives, news and strategies from leading experts in healthcare finance. For show notes and additional resources from Besler Holdings, visit https://www.besler.holdings/podcasts.

  1. Oct 14

    From CFO to Cancer Research–A Conversation About Challenging Assumptions [PODCAST]

    ← Back to All Podcasts From CFO to Cancer Research — A Conversation About Challenging Assumptions In this episode, Ted Giovanis, President of the Jayne Koskinas Ted Giovanis Foundation for Health and Policy, discusses from CFO to cancer research, a conversation about challenging assumptions. Highlights of this episode include: What drives hospital CFOs to keep taking on entirely new challenges One thing about how healthcare operates today that we should fundamentally rethink A question about healthcare we’re still not asking Return on investment when it comes to scientific research that may take years to pay off Which is more expensive for healthcare, trying something new that might fail or continuing to do things the way we’ve always done them? What lessons to apply for improving healthcare and cancer research Subscribe Today! Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome Ted Giovanis. Ted has been the president of the Jayne Koskinas Ted Giovanis Foundation for Health and Policy, which conducts research in metastatic breast cancer and health policy. He is also a professional race driver and team owner in the International Motorsports Association Racing Series. Examples of health policy research that their foundation has conducted include research on the value of hospital tax exemptions relative to hospital-provided charity free care, how to explain health plan prices and quality information to individuals with varying degrees of numeracy and literacy, and defining meaningful quality measures, including the weighting of those measures into aggregate measures for communication to patients. While in practice, Ted was involved in several legislative efforts that resulted in the establishment and implementation of several payment mechanisms, including the Medicare Geographic Review Board and Section 508 reclassification process, the policy for the payment of the certified registered nurse anesthetists, and the long-term care payment systems for various states. Most notably, Ted discovered and prosecuted the Medicare budget neutrality error, which was the basis of the rural floor budget neutrality appeal and related settlements that at the time was the largest settlement Medicare had lost. In this episode, we’re discussing from CFO to cancer research, a conversation about challenging assumptions. Welcome, and thank you for joining us, Ted. Ted Giovanis: Oh, thanks, Kelly. Thanks. Good to be here. Kelly: So, let’s go ahead and jump in. So, you’ve been a hospital CFO. You’ve helped shape healthcare policy, been part of a landmark court case, written books, and now race professionally and fund cancer research. What drives you to keep taking on entirely new challenges? Ted: Well, that’s a really good question. So, I can tell you as far back as I can remember, I’ve had this drive to achieve. Maybe it was the fact I was an only child, and we didn’t have any money. But to achieve, you need to be very goal-oriented. And in this sense, I’m the typical Capricorn. I set goals and I locomote towards them. I started in healthcare and finance and worked my way up, setting goals all the way along the line. And somewhere around 1978, I became acquainted with a guy named Mike Vance, who was an influential thought leader and author. And he was the one that instilled in me a commitment to a lifetime of continuous learning and growth. And ever since then, that’s sort of what I’ve been doing. That curiosity has led me to ask a lot of questions that others wouldn’t ask, which brought me to the lawsuit, ironically, and has also led me to cancer research. So, asking questions prompts you to try to find the answers. And if you don’t know the answers, you talk to other people and you try to find them from them. So, you look up to people that can give you the answers. So as a bonus, as it turns out, as you age, learning more and staying mentally active is a big plus. A long time ago, Henry Ford once said, “Anyone who stops growing is old, whether that happens at 20 or 80.” I just turned 80, and I don’t plan on stopping anytime soon. And Henry Ford also said, “Anyone who keeps growing becomes more valuable, regardless of physical capacity.” So, I hope I’m becoming and learning and growing and becoming more valuable. Kelly: Yeah, I love that committing to a lifetime of learning and growth. That is great advice. After decades in healthcare finance, what’s one thing about how healthcare operates today that you think we should fundamentally rethink? Ted: Well, I think there’s one thing we need to rethink. It’s actually how to lead there’s a lot of people in healthcare today that are talking about being patient-centered, patient-centric, but too often they don’t think patient-centric in the way they make decisions. So, we need leaders willing to challenge the status quo. And more importantly, willing to be introspective, look within oneself of how they can improve. And remember, remember the definition of insanity is doing the same things over and over again and expecting something different. And I think that’s what we do a little bit. I support now much research. And so, I can use that as a little bit of an example. The goal of most healthcare research is ultimately on our side, is to help patients, to find cures, to determine better treatments. If we look at healthcare organizations, there’s things that they can do to lead and to streamline things, including in the administrative cost area, in the near term. To me, indirect costs are something that we can manage now. In many cases, they’ve got out of control. There’s a lot more to do all the way along the line, but I think indirect costs are something that we can deal with to get started. Kelly: No, I love what you said about challenging the status quo. I think that is really important, especially in healthcare. Ted, you’ve often said that breakthroughs start with asking better questions. What’s a question about healthcare that you think we’re still not asking? Ted: That’s a good question. The question we’re really not asking is, do we really understand how X or how something works, or are we assuming too much? I mentioned before, putting patients at the center, that to do that well, we need to understand what those patients are experiencing virtually at every level, from diagnosis, treatment, to billing, and follow-ups. So, for me, I’m looking specifically at breast cancer and within breast cancer, specifically at metastasis. How does it spread? Why does it spread? And we’re down into the minutiae of intercellular communications. But as a country, we don’t fund research in basic science to find out these kinds of things and to find out how things work. We tend to ask questions we think we know the answers to, but rarely do we throw money behind something that we truly don’t know or understand. And so, I think we’ve got that a little backwards. If we know how things work, then we can model it and we can experiment in the model to identify a path to diagnosis, treatments, and prevention. We really need to change our thinking. And I’ll paraphrase it in racing. There’s a concept called ocular driving. You drive where you look and where you can see. The farther you can see ahead and anticipate, that’s where you’ll go. The same thing is in healthcare with our thinking. We need to change our frame of reference and our thinking. And so that’s sort of the framework that will let us design patient flows of the future. And those patient flows need to be adaptable. Because the one thing is for sure, care will change again within the next decade. And so, adaptability and resilience is going to be key. Kelly: Yeah, no, I love what you said about we have to change our thinking. I think that’s very true. As a former CFO, how do you think about return on investment when it comes to scientific research that may take years to pay off? Ted: I’ve learned that the best return on investment comes from understanding how things work first and then leveraging on that knowledge. That’s true in racing and it’s true in research. And I’m sure it’s true in healthcare organizations and in the provision of care. In racing, it’s how you get an edge on your competition. At first, you look for the bigger things, and of course, you take care of them. But over time, it’s the small adjustments, the steady improvements that combine to improve your performance. We take the same approach to research. We invest in foundational science and talented people who ask the right questions or challenge the status quo. It’s investing early before answers are no, and that’s important. Those investments may take some time to pay off, but they create the knowledge that foster future breakthroughs. And we need to be good financial stewards. It’s about making investments today that make some things possible tomorrow. So that’s sort of the mantra that we’ve adopted in our foundation, knowing how it works. Kelly: That makes a lot of sense. So, which is more expensive for healthcare? Trying something new that might fail or continuing to do things the way we’ve always done them? Ted: I think, Kelly, first of all, it comes back to maybe it’s another problem with our thinking, and that we are afraid of failure. Finding out you’re wrong isn’t a failure. It’s information. It’s learning. It tells you where to adjust before you’ve invested years heading in the wrong direction. So, research, metaphorically, is like moving a football down the field. You can’t score without first moving the ball and without investment at the beginning of a drive, so to spea

  2. Oct 2

    Locking Down Corporate AI Usage Webinar

    ← Back to All Podcasts Locking Down Corporate AI Usage Webinar In this episode, Jason Nadal, Besler Holdings’ and Sypher Security’s Information Security Officer, will provide us with a glimpse into the next Hospital Finance Academy Webinar, “Locking Down Corporate AI Usage,” live on Wednesday, October 7th, at 1 PM ET. Highlights of this episode include: How companies deal with artificial intelligence and how they should make the decision to embrace this technology What the benefits and detriments of AI usage are What tools out there to help protect your company and your data What other challenges you have in keeping aware of AI usage How you manage third parties not directly under your control The key takeaways Subscribe Today! Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome back Jason Nadal, Besler Holdings’ and Sypher Security’s Information Security Officer. In this episode, Jason will provide us with a glimpse into our next Hospital Finance Academy Webinar, “Locking Down Corporate AI Usage,” live on Wednesday, October 7th, at 1 PM Eastern Time. Welcome back, and thank you for joining us, Jason. Jason Nadal: Hi. Thanks for having me. Kelly: All right. Well, let’s go ahead and jump in. So, we know artificial intelligence is everywhere now. How should companies deal with this and make the decision to embrace this technology? Jason: Well, if you run a company right now, somebody on your team is likely already using AI. So ideally, that would be via an approved path that you have already set up, but maybe it’s just a browser tab they opened up at lunch, putting something in Google and getting AI results. Either way, the question is not, “Should we use AI?” It’s already embedded in a lot of the approved corporate tools that are already out there. So, the question is, “Do we know what we allow, what we forbid, and how do we keep that promise when the tools keep changing under our feet?” So those are the kinds of conversations that security and IT folks have when leadership asks for a practical plan around AI. So, over the next 10 minutes or so, I’ll walk through some of the benefits and risks. We’ll get into that a bit deeper during the webinar that’s upcoming, but this will give you a methodology of control you can actually run, some of the categories of tooling that support it, and the challenge of feature creep in tools that you’ve already approved. And we’re also going to look at how a vendor and open-source software assessment has to catch up. Kelly: Yeah. I mean, it is really everywhere. It’s embedded in everything now, it seems like. [laughter] Yeah. It’s a lot to keep up with. So, what are the benefits and detriments of AI usage? Jason: Sure. There’s a lot of benefits, and there’s definitely a lot of detriments as well. So, AI earns its value when it shortens the work that you’re already doing, especially that work that used to waste a lot of your time through just tedium, repeated tasks, and things like that. So, I find it really shines at drafting, summarizing, searching or researching, coding assists, and also triaging helpdesk tickets. So those are real-time gains when the data and the use case match the risk. So, in healthcare and adjacent work, that might be a little less clear. So, a nurse or revenue cycle analyst can summarize a long chart note, draft a patient letter, or speed up some prior auth paperwork. A cost report or appeals team can find patterns faster. So done carefully, ideally with this human oversight as to what’s produced, that is time returned to care and to accurate billing. But the downside is just as concrete. So, paste the wrong note into a public chatbot, and you may have moved protected health information, PHI, or something else confidential or sensitive, outside your control. So, a helpful summarizer can invent a fact, called hallucinations, that then gets treated like clinical or financial truth. There’s really a huge downside to that if it’s not checked over by humans with clinical experience. An automation that writes into scheduling, ticketing, or an EHR-adjacent system can turn a bad model answer into a real patient or operations problem. Outside of healthcare, the pattern is much the same. So, marketing could paste customer lists into a public model. Finance could paste financial forecasts. Engineering could paste source code or API keys, maybe in a hurry or just this one time, and leak information that you don’t really intend to leak. Legal can paste contract language. You get the benefit of speed, but the detriment of leaking your data, over trusting the AI, and a trail that, once it’s out there, you can’t really tidy it up after the fact. So, a key point to establishing governance is having frank discussions of what data is acceptable to this risk if it were to leak. I really can’t say that one enough. Kelly: Yeah, I mean, I know that in marketing we use it quite a bit, but I mean, you all help us really understand what we’re really in for there. So, I know there’s a lot to keep in mind. So how do you lock this down without pretending people will stop being curious? Jason: So yeah, you do need this methodology. The first thing I’d say, write an AI usage statement. This is your company’s position on how AI is used. Let it have plain language that’s easily readable. And this company position will include what interactions are allowed and what are not. Who’s able to use what classes of AI? What data classes may never leave the building? It may not just be PHI or employee data. It could be financials, as we said before, or just confidential mergers and acquisition information. So, what AI interactions require a human in the loop? What happens when someone isn’t sure? They should always be trained to ask before they just paste data in somewhere. Publish this conspicuously, train on it, and make sure that people know what’s appropriate to do with their AI. Refresh it when the landscape moves. So, if you don’t have a written position, every employee is going to have their own assumptions on what is good or bad. That’s not really empowerment. That’s just risk that’s out there unmanaged. I’d also recommend don’t write this usage statement from scratch. See what others in the industry, especially your industry, are doing, and tailor what’s out there to yourself. Secondly, you should assess the AI that is in question, the AI that you want to use in any given situation. When a third party uses AI in a product that you buy, treat that as part of vendor due diligence. Ask the vendor, “Where are these models running?” Ask whether the prompts or the outputs of those prompts are retained with them or are they used for training. Ask about sub-processors. Maybe that vendor is using somebody else to do their AI work. Ask also whether AI features can write back into your system. Don’t just accept a blanket, “We’re AI-powered,” as a checkbox. You need enough clarity to decide, yes, this is an acceptable risk. No, this isn’t going to work for us. Or yes, but we need these conditions in place to feel good about the risk of using this tool. And keep logs. Review those regularly. What is not AI today might become AI tomorrow. I’m sure all of us have seen an application that we’ve used online that just, after approved, suddenly has new AI functionality. So, train your users to notice new AI functionality added to the products that they already use. Third, you want to control access to your systems. And there are different types of access that you need to be aware of all three of these and looking into where AI touches all of these. First off, private access. This is ideal if you’re using sensitive data. Your employees would then be using AI that is hosted locally within company boundaries. Private model and private instance, your network. You can still govern who can use it, what data they may feed it, and how you log that use. Just because it’s private doesn’t mean it’s unsupervised, but at least you can keep the inner boundaries of where that data can go. Next up would be public access, people reaching third-party AI sites out in the open internet. So, you decide who can get there under what policy and how that policy stays current when new sites appear every week. So, blocking everything forever, that’s rarely an answer. But blind open access is worse. Pick that controlled path and make sure you maintain who has proper access to it. And internal access is different from private. So, this is AI that’s baked into platforms you’ve already approved. Productivity suites, especially CRMs, ticketing, EHR add-ons, collaboration tools, all of these are things that we’ve seen ripe targets to add AI functionality to. Again, the purpose is to make them easier to use, but you need to make sure you maintain the risk of that if it wasn’t there when you initially assessed that vendor. So, it could be somebody just flipped a feature flag or a vendor released a sidebar assistant. It’s not really a new public chatbot to evaluate from scratch, but there could be changes to what models are being used and the risks associated with that. So, you should treat it as a change to an approved system. You should have that same change management, the same risk review that you do for a new vendor, the same data classification questions. So, if you’re only policing public websites, you’re going to miss that AI that arrived inside your door because you’ve already let it in. Fourth, control AI access to your data. The data classification is very important. Label what your data type is. Is this file public? Is this one confide

  3. Sep 30

    Healthcare Has a Revenue Problem, But It's Really a Decision Problem

    ← Back to All Podcasts Healthcare Has a Revenue Problem, But It’s Really a Decision Problem In this episode, Angelica Landers, Healthcare Executive & Growth Strategist, discusses how healthcare has a revenue problem, but it’s really a decision problem. Highlights of this episode include: Before a hospital or healthcare organization launches a new service line, what financial questions should leadership answer first How to determine whether the service is actually worth offering Will the service actually make money? How to determine whether your payer mix can support a service line or business model before you invest significant capital into it How healthcare organizations can build stronger relationships with their payers to improve reimbursement and resolve issues What a true service line profitability analysis looks like What the financial and operational questions you want answered before you ever get to the purchase price When a healthcare organization is trying to grow, how do to decide whether to build internally, acquire another organization, or partner with someone else Subscribe Today! Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome Angelica Landers. Angie is a healthcare executive and growth strategist with more than 18 years of experience working at the intersection of healthcare operations, sales, M&A, revenue cycle, technology, and startup growth. Her experience spans provider organizations, MSOs, DSOs, digital health, telehealth, healthcare technology, and high-growth startups. She has directed 58 concurrent M&A integrations, managed revenue cycle operations generating up to $45 million in monthly collections, sold more than $500 million in managed services agreements, and built scalable operating models for healthcare organizations navigating growth and transformation. Angie brings a unique perspective that connects the financial decision to the operational reality behind it. Her work includes acquisition strategy and integration, revenue cycle transformation, payer and reimbursement strategy, healthcare commercialization, P&L and financial analysis, operational scalability, strategic partnerships, and startup growth. Through Alleviate Strategy & Solutions, Angie advises healthcare executives, investors, founders, and growth-stage organizations on the systems behind performance, helping them make better decisions about growth, acquisitions, technology, operations, and revenue. In this episode, we’re discussing: Healthcare has a revenue problem, but it’s really a decision problem. Welcome, and thank you for joining us, Angie. Angelica Landers: Thank you for having me, Kelly. I’m so excited to be here today. Kelly: Yeah, we’re excited to have you. Well, let’s go ahead and jump in. So, healthcare finance isn’t just about collecting the money. It’s about making better decisions before the service ever happens. Before a hospital or healthcare organization launches a new service line, what financial questions should leadership answer first, and how do you determine whether the service is actually worth offering? Angelica: When everyone first proposes this question, everyone automatically assumes demand or growth equals revenue. And when everyone assumes this, before everyone can get their answers out, the CFO walks in and asks the most difficult question, but I would say the most correct question. Will this service actually make money, given our payer mix, our cost structure, and our referral patterns? Or, in just the shorthand question, is this a profitable demand? Will we make money, or our ROI off of implementing this new service? So, a service line can have strong community need, excellent clinical outcomes. Your neighbor practices might be doing this, and you might have heard of their uplift in revenue. You might have heard of their growing patient population. But are those transferable to your practice is the question. Before launching any new service, leadership must determine whether the opportunity creates that sustainable economic value within their practice. So, the goal is not simply to generate revenue. The goal is to generate revenue that exceeds the cost of care. By the time a claim reaches your billing department, leadership has to make these decisions beforehand that determine whether that claim is profitable or payable. So many healthcare organizations, to start with demand is great, but we should also look at margin. Kelly: Right. No, I mean, I love what you said. I wrote it down. Will the service actually make money? It’s a great question. Angelica: Yeah. Kelly: So how do you determine whether your payer mix can support a service line or business model before you invest significant capital into it? Angelica: Yeah, so I would start with the obvious question, is there really a revenue opportunity? There’s a series of analyses and just questions that leadership should go through, grouped together with their committee, their investors, and really go through each variable of economic value. So, starting with, obviously, what service to offer? Everyone is being innovative in the healthcare industry. Within tech, the startup rise of telehealth, value-based care, I mean, all of this brings different payment models, different strategies, different positions you can bring to your practice. But the key question here is, does this service create strategic and financial value, again, to your unique situation? Not every clinical service creates that economic value. Some services just generate direct profit. They create downstream referrals, straighten payer relationships, even support other strategic growths. So, looking at just the variable of, ‘How much does this service make by revenue position?’ isn’t the entire story. Leadership should evaluate community need, of course, competitors’ offerings, strategic alignment. But a service with moderate demand and strong reimbursement may outperform a high-demand service with weak reimbursement. I would say look at both the economical value and also the community need and demand that comes with it. Kelly: That makes a lot of sense. And I think the bottom line that I kept– and the word I kept hearing over and over again was value. So that’s definitely key. So beyond negotiating the contract, how can healthcare organizations build stronger relationships with their payers to improve reimbursement and resolve issues? Angelica: So, payer collaboration does not end after a payer contract is executed. It’s just the beginning. Your payer contract director should not be the only one talking to your payers. This is a collaboration between RCM, your payer contracting department, and really with a dotted line to finance through RCM. Within each contract, you are assigned a provider relations advocate, which is the bridge between your practice and the insurance company. Many organizations only contact payers when there’s claims denying or, obviously, when contract negotiations are up for renewal. But high-performing organizations treat payers as strategic partners. You can contact your provider relations advocate when there’s prior authorization problems, when there’s an increase to your denial trends, when you’re having coverage or network access issues. But they can also help you leverage strategies that you’ve never heard of, like good-faith appeals, payout negotiations. They can also help you while you’re transitioning through billing companies, or also help you with provider education when you’re dealing with referrals and orders coming from or referring providers. When problems occur, there’s always a relationship in place. And that’s why it’s smarter to do this early on in the contracting phase. The best reimbursement strategy is often operational excellence, not aggressive contract negotiation. Kelly: Yeah, and I mean, those relationships are key there. It makes a lot of sense. So, healthcare leaders often know their revenue. But do they really know what it costs to deliver that revenue? What does a true service line profitability analysis look like? Angelica: So, this is referred to as a cost analysis. The main question we ask when performing this analysis is, how much does each service actually cost to deliver? Only after understanding this margin should expansion decisions be made within leadership. One of the most dangerous questions in healthcare is: what’s our revenue, or where is it coming from, or what is that profit margin? Without asking what is our cost per unit of care, we’re not really understanding that profit margin just yet. Many organizations obviously know their charges, their collections, their net revenue, but they’re not doing the deeper analysis of cost. So, cost per patient, cost per visit, cost per procedure. A true service level profitability analysis includes revenue, direct cost, indirect cost, and even deeper dives into those fees of those indirect costs that ultimately get calculated into the cost of care. Cost analysis also includes what volume is required to break even. So how many patients, study visits, or procedures are required before we start losing money? Also, we would like to include in that analysis what is required to generate that profit margin. So, it’s not so much if we schedule it, but do we have the staff, the tools to render that service? And all of that is included in that indirect cost that we perform during that cost analysis. Kelly: Yeah, that sounds like a pretty important process. I know that the profit margin is really important. So, Angie, when you’re evaluating a healthcare acquisition, what are the financial and operational questions you wan

  4. Sep 23

    The Growing Denials Crisis and What Healthcare Leaders Can Do

    ← Back to All Podcasts The Growing Denials Crisis and What Healthcare Leaders Can Do In this episode, Noah Breslow, CEO of Revecore, discusses the growing denials crisis and what healthcare leaders can do. Highlights of this episode include: Why denials are becoming such a significant challenge for health systems What the financial implications are on health systems Why so many organizations struggle to prevent denials before they happen What the biggest reasons denials continue to slip through the cracks How health systems can shift from reacting to denials to preventing them How AI and automation can help identify and address denial risks earlier What roles dedicated denial prevention processes play in improving outcomes What revenue cycle leaders should do now to strengthen their denial strategy Subscribe Today! Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome Noah Breslow. As CEO of Revecore, Noah brings more than 20 years of executive leadership experience with a focus on driving growth, innovation, and transformation in complex, highly regulated industries. Most recently, Noah was a partner at Bain Capital Ventures, or BCV, where he led their portfolio support team, built out data-driven investment tooling, and helped incubate two startups at the forefront of applying AI in the insurance claims processing and wealth management industries. Prior to BCV, Noah served as chairman and CEO of OnDeck, a pioneering online small business lender where he built the business from its earliest stages, took it public, and ultimately facilitated its acquisition. Earlier in his career, Noah held leadership roles in product, engineering, and marketing. He holds a Bachelor of Science in Computer Science and Engineering from MIT and an MBA from Harvard Business School. In this episode, we’re discussing the growing denials crisis and what healthcare leaders can do. Welcome, and thank you for joining us, Noah. Noah Breslow: Thanks so much, Kelly. It’s really great to be here. Kelly: It’s great to have you. Well, let’s go ahead and jump in. So why are denials becoming such a significant challenge for health systems? And what are the financial implications on health systems? Noah: Yeah, it’s a trend that’s obviously been there for a long time. But it’s getting worse and worse. So, denials have really moved from a back-office kind of nuisance to a real top-line, front and center margin issue. So, research from McKinsey shows that nearly 3% of net patient revenue is written off due to clinical denials alone. And then if you add in underpayments, the cost of appealing those denials, timely filing issues, you might get another percent or two as well, hitting hospitals. So, I think you have a big financial set of changes going on, and we can get more into that. And then you’ve also got the fact that payers have gotten a lot more sophisticated. So, they’re using AI to do AI-driven claims review, deny claims in a more automated way, in a more nuanced way, maybe than they did before. And we’re seeing just denial trends going up across the board. Kelly: Yeah, I mean, I know denials are a huge issue with such significant financial implications. So, Noah, why do so many organizations struggle to prevent denials before they happen? Noah: It’s got a variety of reasons here. I think organizations struggle to prevent denials, not because they don’t intend to stop denials. So, 47% of organizations cite improving clinical denials as a top priority, yet only around 36% have standardized processes to actually do it. So even though they want to make this an issue, actually implementing the process and the infrastructure to better manage denials is more of a challenge. The other thing about denials is you can obviously engage in that firefighting motion, right? You get a claim denied, you appeal the claim, you go back and forth to adjudicate that one claim. That’s a very different thing than fixing that root cause of the denial upstream. And I think most organizations are better positioned to do that firefighting on a claim-by-claim basis than really do that systemic analysis. “Why is this denial happening? What process do I have to fix on patient intake, or on clinical documentation, or on billing and coding to make sure that that denial doesn’t happen again in the future?” And that fragmentation is a huge challenge for hospitals. Kelly: Yeah, it seems like doing that hard work is key there. So, what are the biggest reasons denials continue to slip through the cracks? Noah: Yeah, I think it’s a multidisciplinary thing. So, you need kind of that combination of data intelligence, the reporting that says, “Hey, we’ve been submitting claims to this particular payer and these types used to get denied at this rate, but we’re seeing this uptrend in these particular types.” You have to connect that intelligence piece. What’s actually happening, and trend analysis, but then you need really human expertise to go, “Okay, why is this trend happening? What could I change upstream to maybe prevent this denial from happening in the future?” And that’s a very multidisciplinary thing. It could involve changing processes. It could involve retraining staff. It could involve system changes, collecting different pieces of information at different points in the process. So, I think it’s that multidisciplinary way to integrate the data on the back end and the intelligence gathering with the process engineering upfront to prevent those denials from happening in the future. Kelly: Yeah, I love what you said there about the combination of data intelligence and human expertise. That totally makes sense to me. Probably to others as well. So, you know how can health systems shift from reacting to denials to preventing them? Noah: Yeah. There’s a few different ways I think health systems can go from reactive mode to prevention mode. First is organizational. You have to set up processes and teams inside your revenue cycle organization that are dedicated, that make it someone’s full-time job to making those structural changes to prevent denials from happening in the future. So, organizations with those dedicated processes to prevent denials have a much higher appeal success rate than organizations who don’t have those dedicated teams. And then the other piece of it is around timing. If you imagine you go to the doctor’s office and they hit your knee with a hammer, and it takes you two months to kick, your reflexes are pretty slow, right? And so, two months later, that procedure happened a long time in the past. The patient has already gone home. The documentation may be locked down. And so working on your feedback loop, that rapid cycle from the moment that denied claim comes in to the trend analysis to going upstream and working to make those changes, it’s a governance question as much as it is a technology question, and denial trends should be front and center in revenue cycle leadership meetings, not something you check in on once a quarter. Kelly: Completely agree. And I love what you said about the reaction mode to prevention mode. That makes a lot of sense in this specific example. So, AI is all the hype. How can AI and automation help identify and address denial risks earlier? Noah: Yeah. So, AI is a tool that payers frankly have a head start on over providers. I think they’ve been implementing AI at scale now for a few years. Providers are starting to catch up, but it’s a little bit of an arms race, and providers really need to deploy AI, I think, to be the best position to handle increasing types of denials in the coming years. So, AI’s real value is pattern recognition at scale, right? Finding those connections across payers, service lines, procedure types that are driving recurring denials faster than someone could just reviewing claims one by one on their own. And so getting that AI deployed to find those patterns is critical. And the other piece, it is a moving target. So, the claims that are denied this year may not be the ones that are denied next year. There are always new types of denials coming in, and some of them can be addressed very basically, right? They could be administrative denials. They could be missing documentation. Those are more sort of straightforward process issues, but there are a lot more subtle ones in terms of the way procedures are coded and billed, the way procedures are bundled together. And that’s where, again, having that human expertise to complement the AI is so important. Kelly: Completely agree. And I mean, it does really seem like providers really need to get on the AI trainer in a major way. So, what role do dedicated denial prevention processes play in improving outcomes? Noah: It’s massive. They have that dedicated team focused on improving outcomes We see it all the time in our client base at Revecore. Some of our customers, maybe the smaller health systems that don’t have those dedicated teams focused on denials, they’re, again, more in that reactive mode, but our larger customers often do have specialized denial teams or executives focused on those. And we’ve seen some of our more sophisticated clients not only have dedicated teams, but have dedicated analytics. So, they’ll know to the analyst level on their team what their overturn rates are by procedure type, by payer, and then they start to actually optimize. So folks on the team who are better at getting certain types of denials overturned will focus there. And then other areas might be gaps that need to be addressed by training or hiring new skill sets. So dedicated team, specific measurement of payer-sp

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If you’re concerned about revenue at your hospital, then The Hospital Finance podcast is your go-to source for information and insights that can help you protect and enhance the revenue your hospital has earned. From regulatory changes to revenue cycle optimization, readmissions to bundled payments, you’ll get important perspectives, news and strategies from leading experts in healthcare finance. For show notes and additional resources from Besler Holdings, visit https://www.besler.holdings/podcasts.

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