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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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-specific trends, procedure-specific trends, and training and upskilling are all a big part of this.
Kelly: I love what you said about the dedicated team. That really is key here. So, Noah, what should revenue cycle leaders do now to strengthen their denial strategy?
Noah: I think the first step is– forgive the phrase. The first step is admitting you have a problem. And you have to get honest about that infrastructure gap. 64% of organizations lack the infrastructure to prevent denials. You can’t do any of this without these processes, dedicated teams, workflow systems, tracking mechanisms. And so, you have to sort of assess what you really have to fight denials and then start to up-level it if you don’t have all of those pieces in place. I think the next thing is really making denial a frontline activity in your revenue cycle team. So, segmenting by payer, by service line, by root cause, making it a recurring executive topic. One healthcare revenue cycle leader I know has daily stand-ups with their team where they read out on the latest trends of denial. So, it’s not a weekly meeting, it’s not a monthly or quarterly meeting. It’s literally every day they’re talking about this. And then I think really looking at that delay between hitting your knee with the hammer and then having a kick, right? So when you see a new trend, measuring your time as an organization from detecting that trend to making that upstream fix, I think if you can do that and work on shrinking that time down, getting really agile and fast with your processes and with your changes, that is the ultimate weapon because denials are always going to be a moving target. It always impairs economic interest to deny some fraction of claims. And so, you have to be moving to where that puck is going every year, every month, every quarter.
Kelly: Wow. Yeah. I mean, I love what you said about the daily meetings. That is certainly an impressive dedication to this issue. Well, thank you so much, Noah, for sharing your insights with us on the growing denials crisis and what healthcare leaders can do. And if a listener wants to learn more or contact you to discuss this topic further, how best can they do that?
Noah: Yeah, no, thanks, Kelly. It’s been great to be here. And if folks want to learn more about what Revecore does to help health systems manage denials and get them overturned and get hospitals the revenue they deserve, they can visit us at our website, https://www.revecore.com, R-E-V-E-C-O-R-E, dot com. Or they can reach out to me directly. I’m just noah.breslow@revecore.com.
Kelly: Awesome. Thank you for providing that. And thank you all for joining us for this episode of The Hospital Finance Podcast. Until next time…
[music] This concludes today’s episode of The Hospital Finance Podcast. For show notes and additional resources to help you protect and enhance revenue at your hospital, visit besler.holdings/podcasts. The Hospital Finance Podcast is a production of Besler Holdings.
If you have a topic that you’d like us to discuss on The Hospital Finance Podcast or if you’d like to be a guest, drop us a line at contact@besler.holdings.
Modern Identity Defense for Healthcare Series—Passkeys in Practice
In this episode, Eric Englebretson, Besler Holdings’ VP of Information Technology, provides us with a glimpse into our next Hospital Finance Academy Webinar, the second in the Modern Identity Defense for Healthcare series, Passkeys in Practice, live on Wednesday, September 16, at 1 PM ET.
Highlights of this episode include:
What we can expect in this second installment in this series?
Why passkeys specifically?
How MFA isn’t solving the identity security problem
Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome back , Besler Holdings’ Vice President of Information Technology. In this episode, Eric will provide us with a glimpse into our next Hospital Finance Academy Webinar, the second in its Modern Identity Defense for Healthcare series, , live on Wednesday, September 16th, at 1 PM Eastern Time. Welcome back, and thank you for joining us, Eric.
Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome and . Nathan is CEO and co-founder of VerifyMedCodes. He leads strategy, partnerships, and go-to market, focused on helping hospitals and RCM teams turn clinical documentation into defensible, denial-resistant revenue. He founded Verify Med Codes to close the gap between what clinicians document and what actually gets paid. We have Angelo, who’s co-founder and chief architect of VerifyMedCodes. He’s a healthcare integration architect with 13-plus years’ experience across Epic, FHIR, HL7, Identity, and Clinical AI. And he’s delivered production CDS hooks and FHIR for value – based care and led ambient AI documentation rollouts across 33, 000 providers. He designed the VerifyMedCodes deterministic PHI-safe coding engine.
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Impact of ‘Failure to Progress’ in Value-Based Care on Healthcare System and Patients
Episode 560
Wednesday, August 26, 2026 • Duration 25:37
In this episode, Theresa Hush, CEO at Roji Health Intelligence, discusses the impact of value-based care's failure to progress in achieving the economic sustainability of the healthcare system and if or what can change the course.
The Revenue Walking Out Your Door--Capturing Wellness Spend at the Point of Care
Episode 560
Wednesday, August 19, 2026 • Duration 16:05
In this episode, Kevin Torf, Co-Founder & Managing Partner at T2 Group discusses the revenue walking out your door, capturing wellness spend at the point of care.
Why Hospital CFOs are Leaving Millions on the Table and What the Best-Run Health Systems are Doing Differently
Episode 559
Wednesday, August 12, 2026 • Duration 25:34
In this episode, James Jacobi VP of Employee Benefits at Hilb Group discusses something that hits every CFO and finance leader in healthcare directly, the runaway cost of employee benefits.
Modern Identity Defense for Healthcare Series--Defending Against Identity Attacks - When MFA Isn’t Enough Webinar
Modern Identity Defense for Healthcare Series: Defending Against Identity Attacks – When MFA Isn’t Enough Webinar
In this episode, Eric Englebretson, Besler Holdings’ Vice President of Information Technology, provides us with a glimpse into Webinar, the first in its Modern Identity Defense for Healthcare Series: Defending Against Identity Attacks – When MFA Isn’t Enough live on Wednesday, August 12, at 1 PM ET.
Highlights of this episode include:
What is this webinar about?
MFA still effective?
How the attacks are evolving
What session tokens are and why you should care about them
Kelly Wisness: Hi, this is Kelly Wisness.We’re pleased to welcome back Eric Englebretson, Besler Holdings’ Vice President of Information Technology. In this episode, Eric will provide us with a glimpse into Besler Holdings’ next Webinar, the first in its Modern Identity Defense for Healthcare Series– live on Wednesday, August 12, at 1 PM Eastern Time. Welcome back and thank you for joining us, Eric.
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A Modern CFO Playbook - OPM for AI, 340B and Patient Engagement
Episode 557
Wednesday, August 5, 2026 • Duration 17:12
In this episode, Jack Risenhoover, healthcare attorney and chair of Velocity Health, discusses a modern CFO playbook for using “other people’s money” to support AI, 340B, and patient engagement initiatives.
Building Trust in Clinical AI--What Hospital Leaders Need to Know About Evidence‑Based Decision Support
Building Trust in Clinical AI–What Hospital Leaders Need to Know About Evidence‑Based Decision Support
In this episode, Dr. Claudine Lott, Physician Executive for Commercial Transformation and Implementation at Elsevier, discusses building trust and clinical AI, what hospital leaders need to know about evidence-based decision support.
Highlights of this episode include:
What ClinicalKey AI is
How AI enhanced clinical decision support tools can help organizations improve both clinical efficiency and financial performance
How AI-powered tools can support clinicians in real time to reduce errors, avoid denials, and strengthen the overall revenue cycle
ROI opportunities for health systems adopting AI-powered clinical intelligence
How AI-powered tools remain evidence-based, transparent, and aligned with clinical best practices
The most common misconceptions hospital leaders have about implementing AI and clinical workflows
Hi, this is . Welcome back to the award-winning . We’re pleased to welcome . She is a board-certified family medicine physician who is passionate about developing and implementing tech-based clinical solutions that improve both patient outcomes and provider experience. As physician executive for commercial transformation and implementation at Elsevier, she supports the development and deployment of their reference products for healthcare providers, including . Dr. Lott received her medical degree from the University of Massachusetts Medical School and completed her residency at White Memorial Medical Center. She served as a primary care physician at the federally qualified Santa Cruz Community Health Center, where she was promoted to site medical director. She then joined Healthcare Startup Crossover Health, where she contributed to the development and expansion of their virtual care model, as well as the creation and deployment of their Patient Engagement Technology Platform. Since joining Elsevier in July 2023, Dr. Lott works cross-functionally to support key initiatives, including customer implementations, product development, and change management.
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EricEnglebretson: Thank you for having me yet again.
Kelly: All right. Let’s go ahead and jump in. So, Eric, the last time you talked about identity attacks in healthcare. What can we expect in this second installment in this series? And why passkeys specifically?
Eric: Well, Kelly, because if part one was about why attackers go after identities, part two is going to be about the single biggest fix we’ve seen in at least 15 years. Passwords are, and I can say this without hyperbole, one of the worst security tools we have for protecting a digital identity. And honestly, passkeys are the industry’s answer. Google, Microsoft, Apple, Amazon, PayPal, if you’ve logged into any of those lately, you’ve probably already been nudged to create one. And this session is going to take the mystery out of what’s actually happening when you do.
Kelly: Yeah, no, I’ve seen a lot more passkeys myself lately, so this will be interesting for me too. So, we already have MFA. Isn’t that solving the identity security problem already?
Eric: So, it does help, but it doesn’t solve it. SMS codes can get intercepted via either SIM swapping and just general insecurities in the protocols behind text messages. The one-time codes you get from apps like Google Authenticator, those can still be phished and replayed if someone tricks you into typing your password and code into a fake site. And then, of course, push-based MFA has what we call and what we identified in the last session as MFA fatigue where people just approve prompts to make them stop. That’s literally how Uber got breached, in fact. Passkeys sidestep all three because they’re inherently multi-factor: something you have, the device, plus something you are or know, like a biometric or a PIN. So, it’s one seamless step, nothing to fatigue approve and nothing to get intercepted and replayed.
Kelly: Very, very interesting. So, Eric, in plain English, what actually is a passkey?
Eric: And this is so fun because at its core, it’s really complicated, but it’s a pair of cryptographic keys. Don’t let your eyes glaze over when I say that. I’ll explain a little bit more in the session. And ultimately, of those keys, one lives on the website server and one lives on your device, and they never trade that secret part back and forth. So, think of it like a locked suggestion box. Anyone can drop a message in using the public key portion, but only the person holding the private key can open that message box and, in this case, sign something to prove that it’s really them. The signature is what gets checked, not a password, not your private key. So, the important bits don’t go back and forth where they could be intercepted.
Kelly: I mean, it sounds easy enough. So, what actually makes passkeys phishing-resistant? I mean, it sounds like a big claim given how easily we can be tricked into giving away passwords and authenticator codes.
Eric: It actually is a big claim, but I think it holds up. So, each passkey you create is bound to a specific domain, and that’s one of the important bits. So, if somebody builds a pixel-perfect clone of Microsoft.com at, let’s say, micronsoft.com and you don’t notice, your device actually won’t even offer the passkey. It actually simply won’t even respond. When implemented properly, there’s no password to type, so there’s nothing to divulge and put in the wrong place. And that one property right there basically neutralizes phishing and the adversary-in-the-middle attacks, which we talked about and were the star villains of our last session.
Kelly: Very interesting. So, healthcare has HIPAA and compliance rules around all of this. Do passkeys actually check that box?
Eric: So, this is great. They don’t actually just check it. They exceed it. So, HIPAA Security Rule requires verifying that a person accessing e-PHI is who they claim to be, but they don’t mandate a specific technology. So, passkeys deliver cryptographic proof of identity, and that eliminates the number one credential theft vector. And that also aligns with, and I’ll explain this as well in this session, something called NIST SP 800-63B. Again, don’t let your eyes glaze over. And basically, they have what are called authenticator levels. And these meet or even go up to the next level depending on whether or not you’re using hardware keys. And then for HHS’s own 405(d) program, they’ve been recommending FIDO2 and passkeys as a priority mitigation for healthcare specifically for quite a while now. So yes, definitely, this far exceeds the things that we need for HIPAA.
Kelly: Well, that is great news. And I’m looking forward to learning more about that. So, this all sounds almost too good. What’s the catch?
Eric: That’s a really fair question. I get it a lot. So, in this case, we’ve got– we’re building a front door that is genuinely rock solid, made out of metal. The catch is actually a backdoor here, account recovery. So as an example, let’s say you’re storing all your passkeys on your phone. If your phone dies and you lose your passkeys, what’s guarding your way back in? Because you’ve got to have one, right? Well, usually it’s a password reset email plus an SMS code. Well, that’s the absolute weakest link protecting the strongest lock we’ve ever built. We’ll dig into exactly how to close that gap in the full session, but that’s really the only downside.
Kelly: Okay. Good to know. So, if someone only takes one thing away from this episode before they join us for the live webinar, what should it be?
Eric: Ultimately, it’s that passkeys aren’t just a nice-to-have. For healthcare organizations, they’re one of the most practical wins available right now against phishing, credential stuffing, and the account takeover attacks that dominate breach reports. In the full session, we’ll walk through the different types of passkeys, where they actually live on your device, device-bound versus synced trade-offs for enterprise deployments, and really an overview of creating and using one. I think it’s going to be well worth your time.
Kelly: Yeah. I think so, too. I think this is going to be a great webinar. Well, thank you so much for joining us, Eric, and for giving us this glimpse into Hospital Finance Academy’s free webinar, Passkeys in Practice, that’s going to be live Wednesday, September 16th, at 1 PM Eastern Time. And as a bonus, you can also earn CPE. Thanks again, Eric.
Eric: Absolutely.
Kelly: Wow, sounds like things are always changing in this space for sure. Well, thank you so–
Eric: Absolutely.
Kelly: And thank you all for joining us for this episode of The Hospital Finance Podcast. Until next time…
[music] This concludes today’s episode of The Hospital Finance Podcast. For show notes and additional resources to help you protect and enhance revenue at your hospital, visit besler.holdings/podcasts. The Hospital Finance Podcast is a production of Besler Holdings.
If you have a topic that you’d like us to discuss on The Hospital Finance Podcast or if you’d like to be a guest, drop us a line at update@besler.com.
In this episode, we’re discussing the money is in the note, not the claim. Welcome, and thank you both for joining us, Nathan and Angelo.
NathanTurock: Thank you for having us.
AngeloSelitto: Thank you for having us. Thank you for the intro, and wonderful to be here.
Kelly: All right. Well, let’s go ahead and jump in. So, VerifyMedCodes started as a coding engine. What problem did you set out to solve, and why do you say the money is in the note, not the claim? And Nathan, I’m going to toss this one over to you.
Nathan: Okay, that’s great. The money is in the note. The way it all works, if we’re going to make it easier for the audience, the progress note that the doctor writes is actually what gets paid by the insurance companies. The way it’s set up in the United States healthcare system is the doctor writes the note, then it goes to a coding or billing agency, and they have to put in all the codes that have been created since the ’50s and ’60s by the insurance industry to make sure it’s accurate so they get paid. The problem with that is the insurance companies have made it so convoluted and so difficult to find all the proper codes.
And I won’t get too into the weeds, but you have your ICD-10 codes, your EM codes, your RAF scores, your HCCs, etc. And it gets very difficult for the physician, hospital, provider to get paid what they’re owed. We created this to make it transparent. So, it goes right from the doctor’s note, we code that the English language, then we code it into the medical nomenclature of actually the entire globe, and then we code it into the coding system that has been created by the insurance companies in the United States to maybe not pay exactly what they should. So, we’re going for clear transparency because I believe that the healthcare provider should get paid what they’re worth, and they shouldn’t be convoluted or changed up by the insurance company just because they want to put all this coding into play.
Kelly: Right. No, I love that y’all made that transparent. I know there’s a lot of complexities in the coding world. So, a lot of AI coding tools make compliance teams nervous because they can hallucinate a code. How is a deterministic approach different, and why does same note in, same codes out matter for revenue integrity? And Angelo, I’m going to toss this one to you.
Angelo: No, it’s a great question. And a probabilistic AI coder can read the same note twice and give you two different code sets. And for revenue integrity, that’s the whole problem. You can’t defend a claim you can’t reproduce. So, our deterministic core is same note in, same codes out every time. And that’s the type of defensibility that we want to offer, right? Is that we have the history, we have the evidence-based, we are giving you the information because of what the note stated. It’s not a hallucination. It’s there in the documents. So, we’re really just carrying it forward, and you’re going to reproduce the same information because the same defensibility and the same information always surfaces. So, it’s just the AI can do its suggestions. It could offer and flag, basically recover anything that was missed and offer options. But in the end, the AI doesn’t have the final say. And I think that’s the difference between fast and defensible.
Kelly: Yeah. No, I love what you said about, “You can’t defend a code you can’t reproduce.” I actually wrote that down because I really thought that that was very interesting that you said that. I love that. So, Nathan, where are hospitals leaving the most defensible money on the table today? Is it risk adjustment capture, denials, or is it somewhere else?
Nathan: It’s in all those, to be perfectly honest with you. The denials is your holy grail, capturing the right amount of money for the service that you provided. The reason being is the insurance companies like to deny a lot. I know everybody out there in podcast land has never heard of an insurance company denying anything.
Kelly: Right.
Nathan: Exactly. So, with that being said, I’m going to sort of piggyback off of what Angelo said and to make this very digestible. Angelo loves when I say it’s an incredibly complex tool that we’ve created, but it’s an A plus B equals C or A plus B plus C equals money. Coding system A is the progress note, which is written in the English language. B is the medical terminology that we’ve also coded into a large LLM. C is all the codes from the insurance companies that we utilize their language against them so they can’t deny. So, we have A plus B plus C equals the correct dollar amount. It’s deterministic. It’s accurate. It’s to the point. So, where they’re leaving money on the table is a couple of different sectors. The first one is first pass rate, which means that the note goes through cleanly and insurance says, “Yep, it’s good to go. We’re going to pay you for it.” The second one is– the big one is denials, which when an insurance company says, “Nope, you don’t have enough data on that. We are denying this for XYZ reason,” it costs money to reprocess that note again.
So, we decrease the first– or increase the first pass rate so it’s a better coding system that goes through insurance and they pay. We decrease the denials because we’re using their language, their wording, and their codings directly against them, directly correlated to the progress note. And there’s also a whole lot of other scores like RAF scores, which is risk adjustment factor, and HCC scores that get very, very complicated, that would drive most coding people nuts and gets lost a lot in the shuffle. With the technology that we have now and with how we coded this, it can’t miss. It’s A plus B plus C, LLM. It’s like a giant calculator. I know, Angelo, it’s a lot more complicated than that. But basically, it’s a giant calculator that makes sure the provider, the healthcare provider, the doctor, the hospital, what have you, gets paid what they’re owed by the insurance company. First pass rate is up, productivity for getting the claim through is increased, and denials go down. Simply put, it’s a giant calculator to make sure the doctors get paid what they’re owed.
Kelly: Yeah, no. I love that A plus B plus C equals the money that you’re owed. So that’s awesome that you guys came up with that. So, Angelo, you catch issues before the claim goes out, missing modifiers, unsupported codes, linkage problems. What does that look like on a real claim?
Angelo: That’s pretty much the bread and butter, right? We catch the missing modifiers, the unsupported codes, linkage problems before the claim goes out, just like you said. And it really looks like a straightforward office visit, 34-year-old, appendicitis. The engine builds the full claim, the diagnosis, six procedures, the levels, the EM. It then scrubs before submission and catches two things the payer would have bounced, one procedure, maybe a lab, an 82565 that needed a modifier 59. And without it, the payer bundles it, and you don’t get paid for it. The EM might have needed modifier 25 to sit alongside the procedure without the denial. There’s denial risk scores at 10 %. Both items flagged with the payer denial reasoning spells it out. And we basically are doing that double-check work. We’re doing that assessment before it goes out. And we also do it before an RCM tech might even see it. So the real capture is that we’re able to surface these as options as well. So, in the deterministic engine that we have, it’s not saying this is the end-all be-all. It’s a really nice system that allows you to see all of the options and see what is missing and what could have been created to build and bundle the exact claim that you guys were looking for or want to execute.
Kelly: Wow, I mean, that sounds pretty impressive there. With CMS interoperability and prior authorization requirements landing in 2027, how should hospital finance leaders be thinking about readiness? And Nathan, I’m going to let you take this one.
Nathan: Okay, pretty much this is the transparency, and CMS is your Medicare, Medicaid. And that goes out to all the insurance companies throughout the United States. So, they want to make sure that this is extremely transparent. It’s fire-based exchange. The clean data is moving between the payers and the providers. So, there is an awful lot of data, and we’re not going to go read all the CMS data points that they’re making up. With that being said, all the hospitals and all the providers and everyone else have to have cleaner capture across the board in 2027. So, the crunch time Angelo specializes in and the team specializes in is that we can help integrate all this into whatever system that they’re running now, either with Epic or any other EHR system that is on the market right now. Simply put, it’s got to be more transparent, easier to decipher, and cleaner data that flows through all this, or CMS isn’t going to pay you, which is going to be a bigger headache.
Kelly: Yeah, I mean, I know transparency is key here, especially. So, PHI safety is a real concern with AI. How do you process a clinical note without patient data ever leaving the building? Angelo, can you help us with this one?
Angelo: Yes, I sure can. So, the concern is real. Most AI coding tools ship the raw note to the cloud, and we don’t, or maybe it’s not to the cloud. It might be a homegrown LLM or AI that they built internal. The deterministic engine runs locally with full access to the note. So, before anything touches an outside model, we do a structural transformation. Every clinical concept is preserved, but the patient identifiers are replaced with typed placeholders. We also have a way of the– basically a backwards communication. So, if something, if they have a question about the local progress note, there could be a communication to say, “Is this a name, or is this–?” maybe it’s the name of a medication, which is another big issue that happens within PHI redaction is that it misses or it hides the name of a medication or anything, a building. And so, what leaves the building is the PHI-free representation, the medicine, not the patient. So, 99.5 % of the clinical content is preserved, and the identifiers don’t travel. That is probably the most impressive piece that we built because it uses a very interesting method to get that data and to transform it, and it’s fail-closed. So, if the gate is ever unsure whether something is safe, if it blocks it, uncertainty defaults to do not send. That’s to a 100 % onshore, and the AI helps us reason, but the medicine never sees who the patient is.
Kelly: Very interesting. I know PHI safety is a real concern across the board. Nathan, if a finance leader listening wants to start small, what is the first step?
Nathan: The first step is just to go on our website and check us out. So, it’s verifymedcodes.com. And the great thing that I designed the website is Angelo comes from the tech side. I’m still in healthcare, but I’m on more of the finance side. So, they can go onto our website and look at the slider scale that we have that can tell how much money that they’re losing on the first pass rate in productivity, in denials, and so on and so forth. They contact with us. We are actually doing right now a 100 notes for free. So, they can send us our 100 worst notes, and we can actually– Well, we’ll process it for them. It doesn’t cost them a dime. And we’ll show how our system is better, faster, more efficient, and will make them more money. So, as a finance person, and I designed this because that’s where I sit in the healthcare sector. I want to know why it’s going to make me more money, why it’s going to make my facility more productive, how much money am I leaving on the table, and how much I’m saving, but want a freebie of a 100 notes or so. So that’s what we offer. We offer the easiest process across the board. So once again, go to verifymedcodes.com, look at our finance calculator, contact us, send us the notes, and we will prove what will work.
Kelly: That sounds like a great offer. Well, thank you so much, Nathan and Angelo, for sharing your insights with us on the money is in the note, not the claim. And if a listener wants to learn more, contact you to discuss this topic further, how best can they do that?
Nathan: Well, they can contact me at nturock, that’s N as in Nathan, last name Turock, T as in Tom, U-R-O-C-K, at verifymedcodes.com. Or, once again, go to the website, verifymedcodes.com, and all our contact information is there. And, Angelo, you can tell them where your contact info is.
Angelo: Yes, thank you, Nathan. Contact info is same. It’s on the website as well. You could also contact me at Angelo, A-N-G-E-L-O, dot Selitto, S-E-L-I-T-T-O, at verifymedcodes.com.
Kelly: Awesome. Thank you both for writing that. And thank you all for joining us for this episode of The Hospital Finance Podcast. Until next time…
[music] This concludes our episode of The Hospital Finance Podcast. For show notes and additional resources, visit us online at besler.holdings. The Hospital Finance Podcast is a production of Besler Holdings; Built on partnership, Driven by success.
If you have a topic that you’d like us to discuss on The Hospital Finance Podcast or if you’d like to be a guest, drop us a line at contact@besler.holdings.
EricEnglebretson: Thank you so much. I’m happy to be here.
Kelly: Well, great. Well, let’s go ahead and jump in. So can you provide a quick overview of what you’re going to be reviewing during this webinar?
Eric: Absolutely. So, the thing that I think is very important for us to cover is that identity has become one of the most targeted areas in all of cybersecurity right now. It used to be that attackers focused on servers or the corporation’s network, and once they’d gotten in from there, they would pivot to get at the thing they’re really after, which is often a company’s data. In the age of cloud computing and remote work, defenses have generally gotten better because traditional defensive methods of defending the network give way to security practices like something called Zero Trust, whereby any interaction with an organization’s resources must be authenticated no matter where a location request might come from. And so, the next logical step is identity attacks. And why is that? Like I said, since attackers focus used to be on breaking into networks and servers, the payoff might be limited. A compromised web server hosting a hospital website might not have any access to any data at all, really, but in today’s integrated environments, one compromised user account. Now that can give an attacker access to email, collaboration tools, patient systems, financial applications, and cloud services, depending on your role. In most organizations, your identity becomes the new perimeter, and that’s why attackers increasingly target people and accounts instead of infrastructure. This is going to be a two-part series covering modern identity security, why attackers have moved to trying to capture identities as a first attack rather than compromised servers, what we can do about it. And in part two, one of the biggest new advancements you’re probably already using in a few places, passkeys.
Kelly: Awesome. Sounds like you’re going to cover a lot during this webinar. I’m really looking forward to it. So, we hear a lot about MFA and how attackers try to bypass it. So is MFA still effective?
Eric: Absolutely. So, MFA really remains one of the most important security controls that has come to us in the past 10 or so years, and it really does stop the vast majority of common attacks, including password reuse, credential stuffing, and other attacks similar to those. The key message here is that MFA is definitely not broken. The message is that attackers have evolved and they’re now looking for ways to get around it. It is just that effective. They’ve got to work around it now rather than just simply trying to use a username and password. And that means organizations need additional layers of protection alongside of MFA.
Kelly: Yeah, so we know that MFA is still effective. So how are attacks evolving to work around it?
Eric: Modern attackers often focus on stealing authenticated sessions rather than stealing passwords. In some phishing attacks, victims enter their credentials and complete MFA successfully, but the attacker captures the resulting session that’s created. Think about it this way. Is it easier for a thief to steal your hotel room key or to try to convince the front desk to issue a new one? In most cases, it’s easier for the thief to steal your room key. After that, they can just come and go as they please, usually without so much as a second glance. We’ve put so many guardrails around the authentication process that attackers are now moving on and looking at what’s behind that, something called sessions and tokens.
Kelly: So, what are session tokens and why should people care about them?
Eric: So, session tokens and they are kind of background… so this is kind of we enter that realm of nerdy a little bit, but stick with me. Session tokens are what keep you log in after you’ve authenticated. They’re the reason that you don’t have to enter your password and MFA code every single time you open an email or click a new page. They’re incredibly useful, but that makes them also incredibly valuable to attackers. If an attacker does steal a valid session token, they may be able to act as though they’re already authenticated without having to have your password again. And that is what makes them so important, and that is why people should care.
Kelly: Yeah, no, that makes a lot of sense. Why is healthcare such a frequent target for identity attacks? I mean, we’ve been hearing so much about this lately.
Eric: Absolutely. So, the main reason for that is that healthcare combines highly valuable data with extremely time-sensitive workflows. Clinicians and staff are constantly dealing with alerts, messages, urgent requests, and attackers understand that environment, and they design their hacking and phishing campaigns specifically to exploit human pressure and urgency. Healthcare isn’t targeted because it’s careless. That’s actually quite the opposite. It’s targeted because its mission creates very unique opportunities attackers can try to exploit.
Kelly: Yeah. I guess having that– always having that sense of urgency probably doesn’t help us in that way, right?
Eric: Absolutely.
Kelly: Yeah. So, what are some warning signs that an account may be compromised?
Eric: So, a few of the things that you should look out for some of those red flags include unexpected MFA prompts, alerts about sign-ins from unfamiliar locations. If you are looking at your inbox forwarding rules, which I recommend that everybody does every once in a while, if a forwarding rule you didn’t set up has appeared and it’s forwarding to some account you don’t know about, that is definitely a big red flag, or just anything that seems off to you that might signify unusual account activity. And one of the most important things you can do here is just to simply report those to your IT staff, help desk, or security staff, whatever your normal workflow is, immediately. Early reporting can often stop a small incident from becoming a major breach.
Kelly: Yeah, no, that makes a ton of sense. Just be more vigilant. So, what’s the next evolution beyond traditional MFA?
Eric: And that is an excellent question. This is something I’m going to cover in part two. The future is phishing resistant authentication. So, there are technologies, and I’m going to use another nerd word here like FIDO2 security keys, Windows Hello for Business, and Passkeys are designed to prevent attackers from stealing or reusing credentials and session information. In part two of the webinar series, we’re going to explore how passkeys work, why companies should adopt them, and how they can dramatically improve both security and user experience.
Kelly: Wow, sounds like things are always changing in this space for sure. Well, thank you so–
Eric: Absolutely.
Kelly: Yeah. Well, thank you so much for joining us, Eric, and for giving us this glimpse into our next free Webinar — Defending Against Identity Attacks – When MFA Isn’t Enough. Join us live on Wednesday, August 12th at 1 PM Eastern Time. And as a bonus, you can also earn CPE. Thanks again, Eric.
Eric: Absolutely.
Kelly: And thank you all for joining us for this episode of The Hospital Finance Podcast. Until next time…
[music] This concludes today’s episode of The Hospital Finance Podcast. For show notes and additional resources to help you protect and enhance revenue at your hospital, visit besler.holdings/podcasts. The Hospital Finance Podcast is a production of Besler Holdings.
If you have a topic that you’d like us to discuss on The Hospital Finance Podcast or if you’d like to be a guest, drop us a line at update@besler.com.
In this episode, we’re discussing building trust and clinical AI, what hospital leaders need to know about evidence-based decision support. Welcome, and thank you for joining us, Claudine.
Dr. Claudine Lott: Thanks for having me on. Appreciate it.
Kelly: Well, it’s great to have you. And let’s go ahead and jump in. So, what is ClinicalKey AI, and how are its new capabilities designed to reduce clinician burden and improve documentation accuracy?
Claudine: So ClinicalKey AI is Elsevier’s flagship generative AI tool that’s designed for clinician use to quickly surface the latest evidence at the point of care to support clinical decision-making. And just to take a step back and provide some context, so here at Elsevier, we’re an almost 150-year-old publishing company. So, for almost 150 years, our role has been as a provider of scientific information and clinical evidence that clinicians can use in their decision-making and in their patient care. And as we’ve moved into more and more clinical solutions, that’s always been kind of our guiding North Star. And so with generative AI coming on the scene, we’ve really thought about, okay, how do we use this emerging technology in our role as a provider of clinical evidence, scientific information to really further that goal of getting clinicians what they need to make decisions and take the best possible care of patients as quickly, accurately, and effectively as possible. And rather than just sort of slapping generative AI on everything because that’s sort of the new thing to do, how do we really leverage this new tool to solve that problem? So ClinicalKey AI is a conversational search tool. The clinician’s able to ask a question in natural language, almost like they might ask a colleague. And then the system goes and searches a curated set of content that we’ve given to it. So that includes much of our Elsevier clinical content, but also some non-Elsevier sources as well, and searches for information and then surfaces that for the clinician. So, it’s not replacing their clinical knowledge or decision-making, but it’s really supporting them by getting the information that they need and we’ve been developing and iterating on this tool for several years now, constantly thinking about how do we make it better and more suited to this clinician use case. So constantly thinking about how we expand our handpicked content sources, thinking about making sure that we always have traceability so clinicians can see where the information is coming from, citation verification, and always thinking about technology upgrades. So, things like privacy, security, and supporting HIPAA compliant use.
Kelly: Wow, that ClinicalKey AI technology sounds really fascinating. So how can AI enhanced clinical decision support tools help organizations improve both clinical efficiency and financial performance?
Claudine: So clinically, the biggest win is what we might call speed to evidence. So, we’re in a situation now where patients are increasingly more complex. Medical knowledge is expanding exponentially. And so, getting that information that is really tailored to the clinical situation as quickly as possible is going to enhance clinical efficiency so that AI enhanced decision support can really surface the most relevant trusted information. In seconds, really supporting those consistent decisions under time pressure and given all those other complexities. In terms of how that clinical efficiency translates into financial performance, I think this is something that we’re going to see continuing to evolve as more and more organizations are integrating these types of tools. So certainly, it makes sense that improving clinical efficiency, improving the quality of care is going to translate into financial performance, but sometimes that ROI can be a little bit difficult to quantify. So, I think that we’re going to see those benchmarks continuing to evolve as more and more institutions are implementing these tools.
Kelly: Yeah, and I love what you said at the beginning, that speed to evidence. I love that. So, what should hospital healthcare system operation leaders look for in the first six to 12 months to know an AI tool is truly delivering clinical value?
Claudine: Yeah, I think this is a great question and something that a lot of both vendors and organizational leaders are really thinking about. Because again, these tools are still new. We’re still seeing how they affect healthcare and how they affect the clinical workflows. And so, we’re still really figuring out how we quantify this sort of clinical value. So, thinking about sort of what can you look for at that 6- or 12-month point to know if your tool is delivering that clinical value. For things like time-saving, improvement of quality of care, those things can be hard to really quantify. And also some of the benefits of generative AI tools, as we mentioned, is that helping clinicians provide faster and better care, it leads to a better experience for those clinicians, for that care team, really addressing that sort of fourth leg of the quadruple aim. But again, that’s something that can be hard to quantify. So, in thinking about, okay, what are some of the metrics that we can sort of look at those sort of checkpoints to see the value that these tools are providing? Certainly, usage metrics are one aspect in terms of just seeing how many providers are using the product, how often are they using it. But that’s only sort of one aspect of it.
Given that there’s more of a– there may be more of a qualitative improvement, some customers and organizations that we’ve seen have chosen to use surveys. So, for example, we had one customer who was utilizing ClinicalKey AI, who did a survey to ask their users after they had trialed it for a given period of time to rate the improvement in their ability to conduct patient care, their confidence in their clinical decision making, and their time saved. And so, they were able to, through that sort of surveying of the users, to sort of quantify the improvements they were seeing in all those areas in that way. And this is also a place where having a clinical champion really involved in the implementation process and in the adoption of these tools can help because checking in with those champions can really connect you to understand, again, some of those sort of improvements in experience that can be a little difficult to quantify. And I think it also comes down to for organizational leaders thinking about what is the problem that the generative AI tool was implemented to solve. So, as I kind of mentioned before, we don’t just want to throw a tool at clinicians just to give them something AI because AI is sort of new and exciting now. We really want to think about, “Okay, what problem are we solving with this?” And from there, then at those checkpoints, I think you have a place to go back and say, “Okay, here’s the problem we were trying to solve. What progress have we made on that?” And use that to kind of quantify the value?
Kelly: Yeah, I know it is difficult to quantify that value there, at least for now. So, it sounds like you guys are making progress with that. So how can AI-powered tools support clinicians in real time to reduce errors, avoid denials, and strengthen the overall revenue cycle?
Claudine: In real time, AI-powered decision support can reduce errors by helping clinicians quickly sort of cross-check their decisions against trusted evidence, or by getting them information that they need to make that decision quickly, especially in an environment that’s high-pressure and time-constrained. In thinking about aspects of revenue cycle management like coding integrity, managing denials, having that grounding in clinical evidence is so vital. Having that documentation that’s based in clear and trusted evidence that’s traceable is really going to provide that sort of grounding and foundation for the decisions that are being made and then the documentation that’s going into that. And that’s going to really support those aspects of the revenue cycle.
Kelly: Yeah, thank you. That makes a lot of sense. So where do you see the strongest ROI opportunities for health systems adopting AI-powered clinical intelligence?
Claudine: So, I think there’s three sort of big ROI opportunities that I see. So first of all, speed, as we’ve discussed, just making decisions more quickly frees up more time for patient care, can help with reduction of administrative burden, and just really free up clinician time. So that just speed is a huge part of it. And then I think the second part is the accuracy and that strong evidence base that I mentioned. So, making sure that decisions are based in strong clinical evidence and that that is really documented in a well-supported way, that’s going to not only support patient care but also those aspects of revenue cycle management that we mentioned. And then I think another opportunity is thinking about standardization. So, there’s definitely an art to the practice of healthcare. So, we may still see some variation in the way that different clinicians might approach the same problem. And having an evidence-based tool has the potential to support more sort of consistent practice patterns across settings. So, I think that standardization and ability to make sure that all care team members have access to evidence on which to base their decisions is another significant opportunity.
Kelly: Sure. Sounds like there are quite a few really strong opportunities there that you shared with us. So how is Elsevier ensuring that AI-powered tools remain evidence-based, transparent, and aligned with clinical best practices?
Claudine: So, as we mentioned, we really anchor clinical key AI in peer-reviewed, copyright-cleared medical evidence. So that includes full-text journal articles as well as journal abstracts, clinical practice guidelines from different organizations, full-text medical textbooks. And we’re constantly thinking about curating that content set, what we need to add, what we want to expand on, how we want to adjust it to make sure that it’s really providing what clinicians need. And we also keep the content current. So, we have a content pipeline that updates every 24 hours. So, the outputs are really reflecting the latest evidence and guidelines as much as possible.
And we’ve really tried to build in that transparency, that traceability, so that the clinician can really see down to the paragraph where that information is coming from. So, they can have that trust. They know that the citation is not being hallucinated or made up by the AI. They can have that trust in where the information is going from, and they can also do a deeper dive if there’s a topic that they want to explore further. So, it really gives them that ability as well. And we use a clinician in the loop approach with a rigorous evaluation framework to continually test the system, follow up on feedback that we get with users, and really just make sure that we’re maintaining and constantly improving the quality of the insights we’re providing.
Kelly: Well, it sounds like that trust is very important to your team there, and that’s appreciated. And you all take that responsibility very seriously.
Claudine: Definitely.
Kelly: Yeah. So, Claudine, from a physician executive’s perspective, what are the most common misconceptions hospital leaders have about implementing AI and clinical workflows? And what advice would you give them as they evaluate solutions?
Claudine: So, there’s three main points about successful adoption of clinical generative AI tools that we’ve seen from our teams and customers, as well as what we’ve been hearing from others in the industry. So, I think these are a great starting point for organizational leaders who are considering implementing a generative AI tool. So first and foremost, as we mentioned before, really knowing the problem that you’re solving with the generative AI tool. So, if you have a generative AI tool, but it’s not solving a problem for the clinician, it’s not making their experience and their care better in some way, nobody’s going to want to adopt that. Nobody’s going to take the time out of their schedule to learn and integrate something new. So really knowing the problem that you’re solving and making sure that you have a tool that fits that.
And so, for us at Elsevier, as I mentioned, we’re seeing this problem of increasing patient complexity, increasing medical knowledge beyond what anyone can sort of memorize. And so, thinking about, okay in our role as a provider of clinical content, how do we use this technology to really solve that problem? So that’s the first part. The second aspect is making sure that the tool is accessible and easy to use, that it’s really embedded in the workflow. Because even if you have a tool that does solve a problem for the clinician, if you’re going to implement something that they have to leave their workflow to try to utilize, that’s not something that they’re going to want to adopt. And certainly, if you’re implementing something because you want to increase their speed and efficiency, if it’s an inefficient process, that’s not going to be helpful at all. So, for us, that consideration goes into things like making sure that our product is integrated into the EHR, having an API option, and basically just making sure that the tool is really in the workflow where the clinician is making that decision.
And the last point is really coming back to this point about trust, because I think some of the misperceptions about clinical AI tools themselves are really related to a lack of understanding of how these tools work. So not understanding that a standalone general use large language model is going to answer clinical questions just based on its training. It’s not actually going to be going out and searching. Whereas a tool that pairs LLM capabilities with retrieval is going to actually be searching and surfacing information in that way. Knowing that some general use tools are drawing from perhaps the whole internet or from sources that are unclear as opposed to a tool that is really clear about where the content is coming from. Risks of using a tool that the privacy protections are not clear. So, all of this sort of lack of understanding contributes to lack of trust, and that’s going to make sure that, again, this is not something that is going to be widely adopted.
And I think that here this is a place where organizational leaders need to think about support from both internal clinical champions and strong vendor partnerships. Because those internal clinical champions, as I mentioned, they’re going to have that deep clinical expertise of the workflow. They’re going to know those problems that the clinicians are facing. And they’re able to be a voice to their peers to say, okay, here’s how this tool works, here’s why it’s trustworthy, and here’s how it’s going to solve the problems that you’re facing. And that’s going to really lead to more successful adoption.
Similarly, having a partnership with a vendor that’s trustworthy, that you’re able to work with them, you’re able to provide feedback and get support for your implementation and your adoption efforts are also very important. And we at Elsevier, as a vendor, really do try to be partners to our customers in that way in supporting them and helping them understand our tools, how they work, how they can benefit them. So those are kind of the three main points that I think are really helpful in thinking about implementing generative AI tools in the clinical setting.
Kelly: Right. It sounds like having those champions and partners are really key to success there. So, Claudine, looking ahead, how do you see AI shaping the future of hospital operations and financial sustainability? And what role will Elsevier play in supporting that transformation?
Claudine: Well, it seems like AI is here to stay, right? So, I think we’re going to, in the future, see AI continuing to lead to changes in really every aspect of healthcare. In terms of clinical decision support, I think we’re going to see these clinical generative AI tools increasingly becoming like a standard layer inside these clinical workflows, so helping clinicians find information, make those quicker decisions, supporting their documentation, but really just with an increasing integration and seamlessness as these tools become more integrated and more widely used. And I think Elsevier’s role is going to be to continue to build on what we’ve been doing all along. So again, constantly thinking about how do we deliver responsible AI solutions that clinicians can trust grounded in that evidence, not replacing their clinical judgment, but really getting them the information that they need in our role as this provider of trusted clinical content and just continuing to think about usability, what features are needed, what content is needed, and how do we continuously think about supporting the clinician with this new technology.
Kelly: Thank you, Claudine, for sharing your insights with us on building trust in clinical AI, what hospital leaders need to know about evidence-based decision support. And if a listener wants to learn more or contact you to discuss this topic further, how best can they do that?
Kelly: Awesome. I will do that as well, and thank you all for joining us for this episode of the Hospital Finance Podcast. Until next time…
[music] This concludes today’s episode of The Hospital Finance Podcast. For show notes and additional resources to help you protect and enhance revenue at your hospital, visit besler.holdings/podcasts. The Hospital Finance Podcast is a production of Besler Holdings.
If you have a topic that you’d like us to discuss on The Hospital Finance Podcast or if you’d like to be a guest, drop us a line at contact@besler.holdings.
