Highlights of this episode include:
- What data stewardship means in the context of revenue cycle and compliance risk.
- How organizations think about the strategic value of internal and external data.
- What proactive monitoring looks like in practice.
- How strong data practices make a difference in a high-risk situation.
- How finance teams can use data to objectively evaluate issues.
- Practical steps toward building a more proactive, data-driven risk monitoring approach.
Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast. We’re pleased to welcome Konstantin Gorelik. Konstantin is an HFMA certified healthcare analytics and operations consultant with over 10 years of experience advising hospitals and provider organizations on reimbursement strategy, compliance risk, and revenue cycle performance. He previously served as a managing consultant at BRG, where he led complex claims analysis, payor provider dispute engagements, regulatory assessments, and multi-hospital monitoring initiatives. Konstantin focuses on data stewardship as a strategic tool, helping healthcare leaders translate internal and public data into structured, proactive risk monitoring frameworks that protect revenue in an increasingly transparent and regulated healthcare market.
In this episode, we discuss how healthcare finance and revenue cycle leaders can use data stewardship and external benchmarking to proactively reduce compliance, reimbursement, and regulatory risk.
Welcome, and thank you for joining us, Konstantin.
Konstantin Gorelik: Thanks so much, Kelly. It’s great to be here.
Kelly: It’s great to have you. Well, let’s go ahead and jump in. So, when healthcare finance leaders hear data stewardship, it can sound abstract. So, what does it actually mean in the context of revenue cycle and compliance risk?
Konstantin: That’s an excellent question, and it’s not the first time or the last time that I get that when I start pitching on what exactly the importance of all of this is. Data stewardship is synonymous in my mind and hopefully in the industry as well with intentional management of how data is collected, validated, stored, and used across the organization. So, to that light, it would allow you to connect your finance, compliance, your operations team, and even your clinical documentation team. It’s not just your IT and their analytics team anymore. In our day and age where everything is becoming more interconnected and interoperable and able to be assessed by not only yourselves internally, if you’re a hospital organization, but externally by any type of group that’s taking a look at you, it’s important to have strong stewardship. It ensures that your reports are defensible and not just informative because honestly, many times you’re going to want to get to the beef of why things are happening at an organization. Numbers work, but numbers also need to tell a good story. And poor stewardship office services during audits, litigation, investigations, which you touched upon when you introduced me, and that’s when it’s the most expensive to fix. A lot of organizations will balk at the fact that they might want to invest a little bit more than they probably should upfront. But then once one of those investigations does come down the line, it’s better that they have done this proactively.
Kelly: Interesting. I really like what you said about intentional management of that. That was something I took down because it just kind of stuck with me. You talk about internal and external data. How should organizations think about the strategic value of each when it comes to mitigating financial and regulatory risk?
Konstantin: So when you hear internal and external data, regardless of what type of organizational vertical you’re in within the healthcare space, so if you’re an RCM, if you are a hospital, if you’re a provider, if you’re a biller or a payer, internal data typically will mean what you have in-house and what you have at your fingertips. So that comes in to you and your organization based on your standard course of business. So hospitals have a little bit of a different flow than maybe a payer would, but the bread and butter of this for hospital finance leaders would be like your revenue cycle data, your claims analytics, all of your metrics that have to do with your dollars and your cents and your bed counts and all the utilization that you have there. It allows you, when you’re internally investigating, to contrast your claims and billing data with past trends and essentially live in a closed container. External data is everything that’s out there in today’s world that wasn’t something that was mainstream maybe 10, 15 years ago, but is now. That includes implementing CMS’s public data sets, which include cost report data. We now have transparency in coverage, which is the payer side of price transparency, which this administration has really flaunted as a way to get transparency for patients. You have hospital transparency data, which is the other side of that type of data, which is the hospitals posting their charges and how much things cost.
And so you have these two juxtapositions of internal and external data, and risk emerges in the gap between your internal performance, which is that closed container of how am I doing this month? How am I doing this year? How many claims did I see this year versus last year? That internal performance, in comparison to external benchmarks is, like I just said, where the risk emerges because you might have a very good view of your own world and your own realm, but if you’re not conscious of everything around you and how you sit relative to peers in the market, you’ll end up in that risky pool, as I like to call it. And external data is particularly powerful for benchmarking, like I mentioned. So, figuring out where you sit as an organization, whether you’re a hospital, a provider, a smaller entity, a health center, whatever it is, versus peers in the market, whether that’s in your area or abroad, also helps you identify outliers. So, if you guys have some sort of– there’s so many outliers that I could probably name off. But for example, you’re identifying conditions that have higher complications than maybe others do in the market for the same one. Like your knee replacements for some reason are 10 times more likely to be complicated.
Those are types of things that maybe internally you, as your organization, can contextualize and understand, but when an auditor or the government is looking at that, they’re going to have questions and those are going to come down the line for you. And when they start asking questions, you got to know how to defend yourself there. And the last piece that external data is very powerful for is, like I said, so it supports or defends your reimbursement position. So context is everything in today’s world, and data is amazing, and there’s so much of it, and it’s beautiful to be able to access all of it, but contextualizing it and marrying it up so that there’s a story to tell will be incredibly beneficial in the years to come as other organizations, namely the government, become more tech-savvy and more proactive with their monitoring and strategy into finding fraud, waste, and abuse.
Kelly: That makes a lot of sense. Thank you for that explanation. Many organizations are still reactive, responding when an audit lawsuit or denial trend appears. What does proactive monitoring look like in practice?
Konstantin: That’s a good question. So, to understand proactive monitoring, you have to also understand reactive monitoring, and reactive in the context of these investigations and things that I’ve been a part of are responding after your denials, for example. So, you have a way that you’ve been billing as an organization for five years, the policies change, you don’t change anything, and then all of your money is hung up in a denial pool. And then now you have to figure out, well, what’s going on here? That’s one way where the reaction comes in. You also have a whistleblower claim that could come in. So that’s your qui tams, for anyone listening who’s in the compliance side of hospital finance, as well as payer disputes that come in. So those are ones that we’ve seen publicly. I live in Massachusetts. We had a public article posted about a dispute between Blue Cross Blue Shield and UMass Memorial Hospital. And those disputes are something that could have been solved privately out of the view of the public if proactive monitoring took place, which sets me up nicely to tell you what proactive monitoring really is.
So that involves routine monitoring of patterns that regulators and payers already analyze. So, I want to let that sink in for anyone listening here. Examples of that would be length-of-stay outliers, unusually high units or charges for certain services, services that frequently trigger outlier payments for anyone in the revenue cycle space. A lot of your contracts will be paid– or, sorry, excuse me, not a lot of your contracts, but generally, there are going to be contingencies in there where, if you have an outlier case, you get paid a certain different rate. We’re seeing in the market and over the past few years, at least in my work with other clients as well, that that triggering of an outlier payment is subject to review and analysis now by payers. So, you might be having your revenue held up because they’re doing that type of investigation these days.
And to get ahead of this type of work, so what does proactive monitoring really look like? There are various aspects that you can take on this. And frankly, I don’t think there’s enough time, even in a podcast, to cover everything that you could do to be proactive, because I believe in the essence of proactivity here. But you can use tools like the PEPPER, which is a report that’s submitted by– or released by CMS and something that hospitals comply with. They flag you for your outlier rating on certain metrics. It’s important to be aware of that type of monitoring. You have cost report trending. So those are publicly available reports that any hospital can download, and you can segment that market so that it fits you as an organization. So, if you are an RCM, a hospital, or a payer, you can take your clients, or yourself, if you’re a hospital, and you can figure out who has a similar bed count, a Medicare percentage, rates of certain type of codes and procedures. There’s all of this data that’s available, and not just the cost support data, but you also have these Medicare fee-for-service data files that are out there and are used extensively by all kinds of litigation firms and investigation firms as well.
So that’s one aspect of it. There are also these very cool new data sets being released that I’m a very big fan of and love playing with. Those are your transparency and coverage files and the hospital price transparency files. So those have ticked in and now are getting more standardized by the government. But now, for the patient side of things, you now have the opportunity to see all of the rates for all of the services that are agreed upon between a payer and a hospital. And so, understanding how you’re pricing and charging for things in disputes with payers and disputes with the government is going to be key because you have to start valuing your services and juxtaposing your value proposition with whether or not the quality is there or whether or not the outcomes are there for what you’re doing. And underneath all of this, so to reiterate, reactive, like I said earlier, is an expensive, expensive process to go in when something hits the fan, and you have to go back for it. It’s a much more expensive process to go in and try to plug all the holes in it when the ship is already sinking, versus going in proactively, which is usually cheaper and less disruptive than those post-event reviews.
Kelly: Wow, so there’s a lot to proactive monitoring, and it looks like it’s pretty important, though. Can you share an example of how strong data practices made a difference in a high-risk situation?
Konstantin: Sure. So, I mean, like I mentioned, there’s many examples of this that we could pull upon from work and maybe even in public news sources. But one that comes to mind is an investigation where I worked. It was a False Claims Act investigation that was triggered by the government. And this was important because it actually came based on the documentation requirements for a hospice. And this case study was important because of the billing and medical record validation that needed to happen. You end up having the government come in for a False Claim Act, essentially saying that you fraudulently have billed Medicare. And so, when that happens, they have their own formula. They have their own extrapolations. They take a small sample. Maybe they found a few things in there. You never know. I’ll never be able to know for certain how they get to it because I’m not ever a part of their investigations at the beginning.
But you end up having an extrapolation, they come to you with a damages model, and then that’s when kind of all the bees in the hive activate, and you have to start reactively looking at this. And so, when you have an allegation of overbilling for an organization like a hospice, for example, they’re not a data-driven entity outright. In today’s world, more organizations are becoming data-driven entities. But here, because it’s something that came to them out of the blue, they were not ready for this. And it required a claim-level validation of all of the visits that they had had with patients over numerous years that the government was looking for audit trails on. And you end up in this situation where this one organization just simply doesn’t have the infrastructure to support this type of investigation because they never thought that this could happen to them. Most people don’t think that something like that could happen to them until the government comes knocking.
And to look and actually look through everything that the government was seeking, we had to combine the billing and the claims data with scanned medical records that were hundreds and hundreds of pages long, admin reports that were generated during the standard course of business. You have to combine that with CMS hospice rate data to figure out about the rates and what they’re charging versus others. And you end up with this project that starts ballooning in effort, scope, and price, frankly, trying to centralize and validate legacy data that are critical because, for the False Claims Act, the only way you can defend against that type of situation as an entity is to actually prove that every single claim is not, in fact, a false claim. So, you have to evaluate each alleged false claim to come back at the government and kind of whittle down that number for them when you’re strategically trying to position yourself. And so, the key lesson that you have there for how strong data practice could have made a difference is that the integrity and the strength of the integrity in your data would determine the legal and financial exposure that you have down the line. So, for a smaller price, by centralizing everything, having everything ready to be analyzed, this wouldn’t have taken hours and hours of consultants, lawyers, deposition hours. All of that adds up a lot for an organization that’s pretty much being reimbursed on a day-to-day basis, right? So that’s just one example.
Kelly: That was a great example. Thanks for sharing it with us. Payer-provider disputes are becoming more common. How can finance teams use data to objectively evaluate issues like charge master increases or reimbursement disagreements?
Konstantin: Yeah, that’s another great angle. So just like I mentioned at the top, with my own home state dispute that was going on between the insurer and the hospital, essentially, the claims data will need to be reviewed internally and externally, and policies will need to be reviewed historically, and contracts will need to be reviewed outright. So those three aspects of it are time-intensive, but proactively doing that will help identify and avoid situations where you end up in a dispute because of contract terms, policies, or actual claim behavior, changes, and anomalies. So, to do that, it’s important for you as an organization to proactively identify your outlier services that are driving disproportionate financial impact, perhaps. You’ll also want to start benchmarking against similar hospitals using cost reports and claims data. So those are publicly available external data sets that you can set to realize and see how things are going. And so, for example, I can touch upon another example. So not exactly what happened in Massachusetts, but in another state that I saw a client and a provider. I was put right in the middle of them trying to figure out what would be an objectively good reimbursement rate. And the finance teams were not quite ready to evaluate the data. So, while the claims data that’s internal to that hospital and that payer were not utilized due to the presence of payer data, it was still used to validate.
So, in these cases, as an organization, like a healthcare organization, like a hospital, that data that you have internally is the gold standard of what you should be relying on. If your data is not as good as what the payer is using, you end up putting yourself at a disadvantage when those things come knocking. You also have the opportunity to investigate the claims data from the payer. So anytime that a claim is adjudicated, the payer will send back those files and those data sets that tell you about what was paid, what was adjusted, and it’s important to have the infrastructure internally to track that type of information, because you have to know why your dollars and why your cents are what they are versus your chargemaster. And the cost report data and the fee-for-service data that I was referencing and alluding to, as well as the transparency data that I talked about, are also key aspects nowadays because the data will bring objectivity where narratives often conflict. So, you’ll have a payer saying one thing, you as a hospital organization will say another, or vice versa, depending on who you are in this disagreement. And so, like I mentioned, again, the context and the quality of your data is going to be incredibly important.
Kelly: Sure, of course. That makes a ton of sense. You know Konstantin, if a CFO or a revenue cycle leader wants to get started, what are some first practical steps toward building a more proactive, data-driven risk monitoring approach?
Konstantin: So typically, when you’re trying to set up a more proactive way to manage all of your risk at an organization, there’s three main pillars that I like to focus on. So, the first is to define your goals. So, is it for compliance purposes? Are you trying to protect your reimbursements, or are you trying to make sure that your bottom line is above a certain level or threshold? Is it an operational insight that you’re trying to glean from this information in terms of blind spots? Once you define your goals, the next set of those pillars I’m going to go into is to set your scope. So, whether or not there are certain service lines that need to be evaluated, if facilities in particular need to be monitored or set up. So, hospitals and health systems are becoming incredibly complex, and they are acquiring and merging and becoming larger and larger entities. And that, by proxy, puts a lot more risk and onus on the organizations that are taking charge of some of these facilities. So being more strategic with which ones you’re monitoring is also incredibly effective because you don’t just want to throw a net over everything when really it could just be a few problem children, we’ll call them for this set. Or outside of facilities if there are risk areas.
So if you have a lot of surgeries or if you as a finance leader are reading the news in healthcare and you see that there are certain investigations that the government are targeting, it’s a good idea to go back and read that and then come back to your data team or your analytics team and be like, “Can I run some of this stuff? Can I figure out how many patients are suffering from major complications in my surgeries that the government considers to be routine.” That type of information. And then once you have your goal and scope, the stakeholders are also the next key piece because those are going to be your legs that make the machine kind of roll. While we are becoming more technologically advanced, I still like the Flintstones analogy where you have a group of people inside of a kind of a wagon and it matters what feet are in there pushing because that’s going to be the quality of your ride, right? So, whether finance, compliance, your RCM leaders internally, externally need to be involved, if the clinical team needs to be involved to help contextualize some of those abnormalities, right? If you have codes that are far and above and you’re in the top percentile in your state for a certain line of [Latin?] procedures or business, you’re going to want your clinical team to come in there and be like, well, this is why X, Y, and Z versus reacting to that later.
And once you have those kind of three pieces, so you have your goals defined, your scope set, and your stakeholders who are going to be helping you, you’ll want to start moving into centralizing and validating the core data sources that you’ll be relying on. So, as I mentioned at the top, you have your internal data sets, right? So that’s what you as your organization steward, manage, and have at your whim, essentially, since it’s your data, versus that external data that you might be purchasing. So, if that’s a CMS data set, something from a commercial vendor, right, like your Komodo Health, your Definitive Healthcares out there, your Kytheras, those types of– IQVIA is a good example of one too. Merging all of that in and combining it into one spot is incredibly important as you start your data-driven risk monitoring.
And the last few things that I want to say on this are pretty straightforward and hopefully no-brainers for a lot of folks who are dealing with this on a day-to-day basis, but it’s important to align your monitoring with CMS and regulatory focus areas. So, if CMS is releasing their information on what they found, what they’ve targeted in years past, that should be on your radar as a finance leader too. It’s not just on your compliance team to be ahead of the curve on all of this, because finance, data, compliance, all of that is emerging in today’s world, and they’re going to be even more intertwined as the years go on. And finally, building processes that are repeatable and refreshed regularly. So not one-off analyses that are siphoned off in Excel workbooks or in someone else’s local drive, but something that is refreshed regularly and repeatable, because you want to be able to have insight and stories to tell as often as you really need it, especially when the judge comes knocking.
Kelly: Most definitely. Well, thanks for providing those practical steps for us. And thank you, Konstantin, for sharing your insights with us on data stewardship as a risk strategy, protecting revenue in a transparent healthcare market. And if a listener wants to learn more, contact you to discuss this topic further, how best can they do that?
Konstantin: So, if anyone wants to reach out and talk about more of what we covered here today, you can reach me via email. So, it’s gorelikadvisory@gmail.com or via LinkedIn. I’m always ready for conversations and love to talk about this information. I think this is such an interesting age that we’re entering in and would be happy to connect with colleagues or anyone else.
Kelly: Wonderful. Thank you for providing that. And thank you all for joining us for this episode of The Hospital Finance Podcast. Until next time…
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