Abby Burns (00:17):
From Advisory Board, we are bringing you a Radio Advisory, your weekly download on how to untangle healthcare's most pressing challenges. I'm Abby Burns. Today we're talking about price transparency. And to be honest, part of the reason we are is that I don't think the majority of healthcare leaders are spun up enough on what is happening in this corner of the policy and market activity. And that's understandable given some of the dynamics we're going to talk about today. Price transparency rules and regulations have been in place since around 2020, but they haven't had a lot of teeth. There's a lot of variability in data quality even within organizations, although that's getting better. But at a time when we're saying healthcare organizations need to be using every tool in their arsenal to navigate some of the tough market dynamics they're facing, price transparency feels like an area that is surprisingly easy to overlook if you're not already steeped in what it is and how to navigate this world.

(01:12):
So today I'm inviting price transparency expert Maria Nikol, CEO of price transparency analytics firm, Revelar Analytics, to help us shed light not only on where things actually stand with price transparency from a rule standpoint, but how healthcare leaders both are and should be using this data to help them with some of their top strategic priorities. Hey, Maria. Welcome to Radio Advisory.

Maria Nikol (01:36):
Thank you for having me today.

Abby Burns (01:40):
Maria, I'm guessing that listeners are coming into this conversation with an incredibly wide range of understanding and experience when it comes to price transparency. Some people are actively using price transparency data today. Some people are vaguely aware there has been some sort of federal rulemaking here, don't know much more than that. Start us off by level setting. When we talk about price transparency in healthcare, what are we really talking about? What is the goal?

Maria Nikol (02:11):
So the goal was originally for consumers to be able to understand what their pricing situation looks like when they go to receive their top shopable services. That was the original intent of the law. The first rules came out in '21, followed by a 2022 rule. There's two sides of it. One for hospitals, so hospitals are supposed to publish their top shopable services. Again, for the purpose of consumers to be able to go look them up. And the second one was for payers to do the exact same thing so that a payer was releasing machine-readable files. Now, most consumers, I would venture to say, are not able to necessarily open up a machine-readable file because they are not machines, nor do they have machines to be able to open them up.

Abby Burns (03:00):
So if the original goal was around consumer shopability, but what we're seeing now that this is actually playing out is that's really not possible. What has the goal sort of evolved into?

Maria Nikol (03:10):
I've not seen the goal necessarily change from a regulatory standpoint. However, what you now see is other stakeholders leveraging this data in a variety of different ways. So some folks and some price transparency vendors are leveraging the data to help consumers understand what that looks like.

Abby Burns (03:28):
Yeah.

Maria Nikol (03:29):
The data is dense. It is complicated. I have yet to find a price transparency vendor that does an amazing job to help consumers understand their cost. However, what I have seen is price transparency vendors help other stakeholders understand what the data's supposed to look like. So you have provider organizations leveraging this data. In contract negotiations, you have health plans also leveraging the same data for similar purposes. Employer groups, sole funded employers as they look to negotiate contracts. And then interestingly, attorneys, law firms, I feel like every week that I'm in this, I find another use case to understand what does fair market value look like in a market.

Abby Burns (04:18):
Yeah. And you're describing stakeholders almost stumbling into finding and being able to use price transparency data. And I am mindful that that is not dissimilar from how you actually ended up in this space. Am I right about that?

Maria Nikol (04:32):
Yes, absolutely. I've spent the last 15 years working predominantly in value-based care for a large payer and helping build their patient-centered medical home program. Then moved over to a startup called Aledade. And then from there, helped to leverage multipayer data to build a performance management system that really helps to understand what does performance look like in value-based care contracts across multipayer contracts. And so we've been working with large data sets literally my entire career, helping organizations leverage those datasets to identify insights. And so having that background, our now chief medical officer came to me and said he was looking to understand what does fair market value look like. Here in Maryland, he is a practicing pediatric urologist working for large and optional MSO. He felt like his codes were fairly on the lower side in terms of negotiation, but had no data to back that up.

Abby Burns (05:34):
Which by the way, is a sentiment that we hear from providers all of the time. "This is what I think I'm experiencing in the market. I don't necessarily have the evidence there."

Maria Nikol (05:44):
Exactly. But how do I find evidence? And so traditionally what you use in contract negotiations is percentage of Medicare, survey data. Now, pediatric urology, that's not the most helpful metric. And so he'd come to me, I told him, "These price transparency files just came out. They're supposed to be consumer friendly. They're really transparent, super easy to understand, publicly available. Go for it." So he comes back probably a week later, so props to him for at least trying. And I encourage everybody else, if you haven't done this, by the way, go on one of these websites, a payer website, a hospital website, try opening these files. What you end up with is either an error message or alternatively do get a table of contents that comes up. There's links within links and some of them are probably going to return error messages. Others, they're going to return unstructured data. It's complete crazy nonsense. And you're looking at it and that's what I did. So I got there. I did it myself. I'm like, "I know there's information that we want in these files, but oh my goodness, there's literally thousands of these files."

Abby Burns (06:52):
To timestamp it, you're talking more in the 2021, '22 timeframe. This is before large language models were an active part of our healthcare environment.

Maria Nikol (07:01):
Yeah. So this is right as interestingly, language models were coming out. I was not using AI for any of this. I just back of the napkin weekend activity, "Let me try to open up these files on my laptop." Which by the way, is not sufficient to actually open up any of this.

Abby Burns (07:18):
And I'm guessing this is what enabled you to see, "Hey, how does the rates for this pediatric urologist compare to the rates that his competitors are getting?"

Maria Nikol (07:24):
That's exactly right. So interestingly, he's the only private practice pediatric urologist in Maryland. And so we did compare him to the large health systems. And lo and behold, we found out that the rates were about three times different.

Abby Burns (07:38):
Wow. I'm guessing he was on the lower end of that.

Maria Nikol (07:41):
He was on the lower end of that, yes absolutely. So that did spark a renegotiation. It was successful. And that's when we realized that others across the country could leverage the data in similar ways across any number of procedures, specialties, codes, including at this point, drug codes.

Abby Burns (08:01):
So Maria, fast-forward what? Three to five years from that time, and now working with Revelar, you are working with this seemingly impenetrable data day in, day out. Before we get into what this looks like today for provider organizations, I'd love to talk about what it looks like for plans. I do want to start with a little bit more of a global view. What patterns have you identified in the data?

Maria Nikol (08:27):
So we've worked with a number of organizations across the country to identify what do these patterns look like. What we usually see is there's a huge variation in pricing. And this is true across all health plans, across all regions. It's not a couple percentage points. We end up with kind of two whole cohorts, if you will. There's a low cohort and a high cohort. Again, with about a 3X variation in any given type.

Abby Burns (08:53):
Wow. So that 3X variation stayed consistent. That was what you originally found.

Maria Nikol (08:58):
Absolutely. It is a consistent trend across the US.

Abby Burns (09:03):
What are some of the unifying factors of organizations that find themselves on the high end and on the low end?

Maria Nikol (09:09):
Yeah. So larger organizations with more resources for negotiations tend to have higher rates that probably will not be surprising anybody. However, even within, as I call them, two cohorts, the low and the high, what you end up with is about a 10% variation. So let's say that you are a large hospital system with resources for contract negotiations, you still have about a 10% variation in your rates, which is really significant when you're talking about a hospital system filling out as many codes as they do on an annual basis.

Abby Burns (09:48):
And that 10% variation might be within a DRG. It's not across all DRGs, it's within DRG variations.

Maria Nikol (09:55):
Yes, yes, yes, exactly. So that's also what we see is, there's going to be a couple codes that are really, really well negotiated, and then everything else is kind of on par. But you know that those are the procedures that they really care about. So you almost see the contracting strategy from these price transparency files. What I also noticed as we started to pull them, we're not just pulling price transparency files at this point. What we've been doing is actually pulling in other data sources. So not just price transparency data, but hey, let's marry that with other publicly available data sources. So NPPES files, other data from CMS, including quality data. So as you bring in publicly available quality metrics, what you end up with is the ability to look at quality and cost in the same application. Interestingly, there's very little correlation between cost and quality metrics.

Abby Burns (10:51):
What you're saying is that higher quality does not lead to higher reimbursement.

Maria Nikol (10:57):
Correct. At that point, it's complete coincidence that that actually happened. So most organizations don't see a correlation between cost and quality. That is extremely helpful. Again, because of my value-based care background, I have to tie this in. Not only is price transparency data helpful in the fee-for-service realm, which is, and that's exactly how we started, most of the work that we've done is on the fee-for-service side where clients are negotiating a contract. They want to understand for that DRG, that HCPCS. "Tell me how the reimbursement looks like. I want to know what the gut across the street is getting reimbursed." When you're starting to look at value-based care contracts, you want to understand, how do I develop a preferred provider network? Price transparency data is absolutely instrumental in developing that.

Abby Burns (11:49):
Do you have any examples of ways that you have worked with a provider organization to help them actually move toward getting fair market value?

Maria Nikol (11:57):
So organizations leverage the price transparency data in two ways. One is you have a fire and an emergency and you're in the 11th hour of your contract negotiation and you want to leverage this data to prove that you are already in line with fair market value or they get increased reimbursement. So we've had a client with that situation. They were already in midst of that negotiation and it was kind of coming to the close of that and they were going to go out of network. I mean, the rate proposal from the payer was completely unsustainable and so they were going to go out of network. And ultimately that's where consumers really get hurt.

Abby Burns (12:36):
Exactly. Bringing it back to the original goal was around consumer shopability. Okay, we're not getting shopability, but it doesn't mean that these two things are completely disconnected.

Maria Nikol (12:44):
That's exactly right. And so they came to us, they're like, "We've leveraged percentage of Medicare. We've leveraged survey data. It's just not getting us to where we need to." So we gave them price transparency data. They were able to successfully leverage that data in a negotiation to come out with a, what I would call a successful contract. They did not go out of network. They were able to keep their rates. It was not a double-digit cut to their rates that was originally proposed. So that was really exciting story for everybody involved really. The health system, the payer, the consumers, I think it was a win-win. And what we were able to find is that others in the market were actually able to get a higher reimbursement on those codes, so they were able to hang on to their existing rates.

Abby Burns (13:33):
That's really interesting when we've been talking a lot on Radio Advisory and at Advisory Board of taking sort of a market view of what happens if other providers in my market start having to rationalize their service portfolio because they're financially unstable and how do those trickle-down effects impact to the other providers in the market? This is a really great example of the opposite.

Maria Nikol (13:51):
Yes, yes, yes, yes, exactly.

Abby Burns (13:53):
So that was one way that provider organizations use this data, the sort of fire drill. What is the other one?

Maria Nikol (13:59):
The other one is I want to keep an eye on what the market is doing, and I want to understand before my contract negotiation even starts, what do rates look like? And most organizations do either quarterly or twice a year refresh up the data to keep an eye on things as they look forward to contract negotiations. You end up being able to do a deeper dive, understand the data a little bit more and really come in with a strategy for your negotiation.

Abby Burns (15:30):
Let's talk for a second about the data quality. You started the conversation talking about how when data came out, it was really hard to use. How usable is the data that provider and plan organizations are sharing?

Maria Nikol (15:42):
The data quality has improved tremendously since it first came out. The reason being is there's a lot of regulations, a lot of sticks, if you will, that have come out over the course since first price transparency regulations came out to make sure that folks are in compliance with these regulations. So what we did is we created a red, yellow, green chart with how compliant is the plan with the price transparency regulations.

(16:08):
So on one end, you have red organizations. Red organizations are non-compliant with the rule whatsoever. The files are not there, the files have not been updated in a very long time. So you can't really use that data. Some of the files are corrupt. Then there's yellow. Yellow organizations have some of the data uploaded and you can derive usable insights out of it. However, some of the files are corrupt. Some of the files are pointing to older files that are no longer up there. You can open up the majority of the files, but not necessarily everything under the sun. So it's usable, but it's not perfect.

Abby Burns (16:50):
Right. It's not super user-friendly.

Maria Nikol (16:52):
Yeah. And then there's green. Organizations that have uploaded the data or posted the data as they're supposed to with, I'm going to say, almost everything perfect. Now, even for green organizations, you still need of usually a vendor partner to help open them. Again, these files are still large. There's still so much repetition in this data that if you're actually trying to open it up on a laptop, it's still not usable. I encourage most organizations not to necessarily build their own system for this. It's just simply inefficient. You need several resources just to maintain these files.

Abby Burns (17:30):
This is actually a question that I was going to ask, which is, how similar are the outputs that you're going to get when an organization tries to clean the data that's posted?

Maria Nikol (17:39):
Yes. So price transparency vendors are not necessarily providing equal outputs. So I'll bring in an example. So we have a client that went to several different price transparency vendors before they came to us. Before they started to use price transparency for contract negotiations, they wanted to verify the accuracy of the data. So the use case was give us our negotiated codes for the largest commercial payer in the market that we know we're in network with. So we know what we're getting paid. You tell us price transparency vendor, what we're getting paid. Let's see if it's accurate.

Abby Burns (18:17):
Yep. A Little QA.

Maria Nikol (18:19):
That price transparency vendor came back and said, "You know what? We are not able to find your TIN and NPI in this data. It's not posted." Well, that's probably not accurate because again, they are in network. We went to price transparency vendor number two. Price transparency vendor number two said, "Yeah, no problem." For whatever reason, they came back with rates that were not the actual negotiated rates for that organization. That organization was like, "Well, wait a minute. If we know we're getting $50 for this code and you're telling us we're getting $60 for this code, that's not right." So they kind of didn't buy the data, no pun intended. And they went to us and we're like, we hear a lot is, "This data is garbage," when organizations come to us.

Abby Burns (19:08):
Yes.

Maria Nikol (19:08):
So no, the data's not garbage. There is a lot of garbage in there. Again, phantom codes, stuff that doesn't make sense. We've had one large payer that had really good data actually, but there is these anomalies in the data. You have a procedure. It's a pretty common office procedure. We're going to say office visit for the purposes of this. It was reimbursed at $7,777,777. You know that's not accurate.

Abby Burns (19:38):
That seems like a cat was stepping on the keyboard.

Maria Nikol (19:40):
Yes. We remove that data. Of course, we always tell clients what we did remove. If somebody wants raw data, we definitely provide it to them with the sevens in there. So again, quality of the data is varied. However, back to my story of the client.

Abby Burns (19:58):
You were sort of vendor number three in this game of this provider trying to find out their rates. How did it end up?

Maria Nikol (20:05):
We did pull the data. We pulled their negotiated codes. What we found was there is some rate variation to these codes for our clients. So we found the rate that they were getting reimbursed. We saw two rates, and so they're like, "What is this two rates? We know we only get reimbursed $50 and change for this code. What about this other number?" So what we do a lot is help organizations understand what they're actually looking at. And a lot of vendors don't necessarily do that. They provide you the data and then you're off on your own trying to figure out what you're looking at. What we do is we handhold them through the process of, "Well, actually in this specific use case, what you have is the MD rate and the APP rate." Now, their APPs weren't doing the service, but in theory, they're contracted to do it.

(20:54):
And so that's why we saw two different rates for this organization, for this specific code. So a lot of the rate variation is we're looking at different modifiers. We're looking at institutional versus professional versus place of service. So you need all of these filters to really understand the data. So a lot of what we do is not necessarily teach somebody how to use a tool, but in this instance, what we teach them is, "Why is there so much variation? I don't understand what I'm looking at."

Abby Burns (21:24):
And what you're getting at, Maria, is really the trust piece because you said earlier that a common reaction to price transparency data, it's all garbage. And it sounds like the needle has moved from, if we were having this conversation a couple of years ago, that would largely be true. Now there actually is insight. It's about, can we extract the insight from what is definitely complicated data? And to use your words from earlier, data that might include garbage, but it is very usable. I want to shift our attention to the plan side of the house, because providers are not the only ones that are using this data. On the plan side of the house, from where I'm sitting, price transparency feels like it could squarely be a threat for health plans or feel like a threat. Help me understand the opportunity side.

Maria Nikol (22:09):
Health plans are absolutely leveraging this data as well. Again, they want to understand what does fair market value look like as they're sitting across the negotiating table. So everybody now has access to this data if they choose to engage with it. Health plans are absolutely leveraging it as well. You want to go into a new market, fair market value looks like we're expanding. Or we're going into a contract negotiation and we want to understand what the other predominant players are looking at in the market.

Abby Burns (22:38):
I could also imagine the opposite side of the coin if plans are looking at, "Hey, we probably need to shrink our service footprint. What markets should we consider exiting based on sort of the revenue opportunities there?"

Maria Nikol (22:49):
Yeah. Yeah.

Abby Burns (22:51):
So it seems like it's fair to say that payers and providers are sort of the quote unquote "Protagonists" when it comes to price transparency data. Why is this also relevant for other stakeholders across the healthcare ecosystem?

Maria Nikol (23:05):
Self-funded employers have utilized this data a tremendous amount, and there's probably more opportunity to do so as we move further into price transparency. So I'm hoping that self-funded employers are using this.

Abby Burns (23:18):
We're hearing a lot of interest from providers in working directly with employers in their market. Could this be an area of partnership or is that not how I should be thinking about price transparency data?

Maria Nikol (23:28):
No, it's a great use of the data. And again, we will see hopefully more and more of this as well. Just healthcare costs continue to skyrocket. What you end up with is hopefully self-funded employers looking to create, again, preferred provider networks and value and system.

Abby Burns (23:45):
Okay. Anybody else that we should be thinking about as end users of price transparency data?

Maria Nikol (23:51):
So attorneys, law firms, they are definitely leveraging this data as well, not just for contract negotiations, but the settlement of out of-network claims. The process is so long, so cumbersome. What we're looking at is helping to shorten that process. Understand, again, any organization, regardless of whether it's a provider, a payer, a self-funded employer-

Abby Burns (24:18):
An investor, I can imagine.

Maria Nikol (24:20):
... an investor, anybody looking to understand fair market value where traditionally they've used survey data, I think is a really, really good use case for price transparency data.

Abby Burns (24:31):
Maria, as we start to wind down, I want to look forward. And first, I don't want to ignore the policy side of price transparency, because this is actually a case where it's been really an instigator of a lot of the activity that we've talked about today, starting back with the executive order all the way to December 2025 when we've had the latest proposed rule. Can you catch us up on what is the latest activity here and what it means for, let's call it the rest of 2026 and beyond?

Maria Nikol (25:00):
So since price transparency rules first came out in '21 and '22, there's a lot of policy that kind of shifted and changed. So number one, enforcement actions have really cranked up. And even last year, there was an executive order that came out middle of last year that really focused on the enforcement side of things.

Abby Burns (25:20):
How much stock do you put in that? And I asked the question because I think one of the criticisms has been there really hasn't been teeth to enforce this stuff.

Maria Nikol (25:29):
I would agree with that. I wish there was more enforcement. Absolutely. However, even that executive order when it first came out, remember that red, yellow, green chart that I'd referenced in the beginning of the conversation? So we've been keeping that for quite some time. Interestingly, organizations actually shifted from red to yellow or from yellow to green just with that executive order coming out.

Abby Burns (25:53):
Wow.

Maria Nikol (25:54):
I'm like, forget the enforcement of it, just the executive order alone actually changed compliance.

Abby Burns (26:00):
And Maria, I failed to ask you this earlier, what does the bell curve of that red, yellow, green look like? Just to give us a sense for what the starting point is as these policies shift folks to the right.

Maria Nikol (26:09):
Percentage-wise, it's really hard to guess or gauge. What I would say is, larger health plans, mostly green. Some of them are a little yellow. And again, it's a judgment call on our end, but the large health plans are really pretty compliant with some data anomalies. The smaller regional payers are not mostly red, but there are definitely some regional payers that are just red. I'm not going to be calling them out today, putting them on blast, but there are definitely red spots, if you will, throughout the US. With that being said, just that executive order alone, without any enforcement whatsoever, created a shift in the right direction towards the green. With that said, there's also other regulations, so not on the health plan side, but on the hospital side as well that are coming into play. So with hospitals, they were originally supposed to publish their price transparency files on their websites. And so what we end up with is just post something.

Abby Burns (27:16):
Yeah. Yep. Let's make sure that this webpage has stuff on it.

Maria Nikol (27:20):
Exactly. Let's just post stuff. There has been not really a rhyme or reason to how it was posted in the original. So all sorts of data files, all sorts of formats, and then they were able to pick their top shopable services. So that was really fun as well. So there was not an apples to apples comparison. It was just the Wild West of price transparency as that has shifted. There's a more unified schema now. They're supposed to be posting real prices. The actual negotiated payment data is now supposed to be posted. We're moving from the hypothetical prices to real money changes that are coming into play with new requirements of the median, the 10th percentile, the 90th percentile. So this really exposes that price variation. It's just not a single number anymore.

Abby Burns (28:08):
Yep. And I believe that was the focus of the proposed rule that came out just a couple of months ago, December 2025.

Maria Nikol (28:14):
Right. And then on the payer side, what we're moving towards is really fixing these large, massive file problems. And we're moving towards network level reporting and reducing all of that irrelevant data that I originally spoke about. So even with that, there's still going to be a need for price transparency vendors because again, even when we decipher and decode and put this data up, organizations are still asking us, "What are we looking at?"

Abby Burns (28:44):
Yeah. The question of usability exists on so many different levels and the policies and the rules and the regulations are pushing toward, "Let's be able to open these files, let's improve the data quality, and let's improve the usability of it so we can get to the right level of granularity." Doesn't mean it's easy to do. You're still talking about massive amounts of data.

Maria Nikol (29:04):
We're moving away from just raw files and being able to decode these raw files as most price transparency vendors have been doing to insights and benchmarking and strategy. And really the winners are going to be those organizations that not only have the data, but those that can actually use that data.

Abby Burns (29:23):
You also teased drug prices early in our conversation. Can we come back there? Where are we? Where do we stand there?

Maria Nikol (29:31):
Yes. So drug prices interestingly are not required to be in there right now, but some health plans are posting drug pricing data. Hopefully we'll have more and more of that in the future. But we are doing work on J-codes right now and it is a fairly complicated topic that we will not delve into as we close things out, but there is some usability to the drug pricing as well. And I'll leave that as the teaser.

Abby Burns (29:58):
Maria, what parting message do you want to leave our listeners with today?

Maria Nikol (30:03):
What I want people to come away with is the data is not garbage. There's really hope to being able to use this data, and I want people to engage with it, whether you find your own price transparency vendor for the purposes of understanding how to use it. Don't ignore it, engage with it, understand it. And hopefully as we move into 2026 and hopefully beyond, we will start to see increased compliance from both sides of the house so that we can actually start utilizing this data in really powerful ways.

Abby Burns (30:40):
Well, Maria, thank you for coming on Radio Advisory.

Maria Nikol (30:44):
Yes, thank you so much for having me today.

Abby Burns (30:51):
Price transparency might have started off as an effort to improve consumer shopability, and maybe, hopefully, we'll get there eventually. But right now, this is something that providers and plans in particular should be using to support your own financial viability. The data isn't perfect and it's not user-friendly, but there's still a ton of opportunity to be had. And that's where vendor partners can make a big difference. As you heard, more to come on improving the quality of the data at scale. But in the meantime, remember, as always, we're here to help.

(31:50):
New episodes drop every Tuesday. If you like Radio Advisory, please share it with your networks, subscribe wherever you get your podcasts, and leave a rating and a review. Radio Advisory is a production of Advisory Board. This episode was produced by me, Abby Burns, as well as Rae Woods, Chloe Bakst, and Atticus Raasch. The episode was edited by Katy Anderson with technical support provided by Dan Tayag, Chris Phelps, and Joe Shrum. Additional support was provided by Leanne Elston and Erin Collins. Special thanks to Morghen Philippi. We'll see you next week.