Babies With NPIs and Other Errors: What’s Wrong With Payers’ Provider Data?

Hello, everyone, and welcome to today’s webinar, babies with NPIs and other errors, what’s wrong with payer’s provider data, addressing the crisis of overconfidence in health plans provider data management. We’re excited you could join us. My name is Megan Billingsley, and I’ll be moderating today’s event. Today, we’ll be discussing recent survey results that could indicate some false confidence in payers’ provider data management strategies and how health plans can help improve their data quality even when they don’t even realize there’s a problem with it. We are thrilled to be joined today by three speakers, Mike Worth, chief commercial officer at ProviderTrust, doctor Tony Threate, senior product manager at ProviderTrust, and Allison Kalis, payer enterprise account development leader at ProviderTrust. Before we get started, I have just a few housekeeping items. Please note the slides will advance automatically throughout the presentation. To enlarge the slides, click the enlarge slides button located in the top right corner of your presentation window. If you need technical assistance, click on the help widget located on the bottom left corner of your console. We encourage you to submit questions at any time throughout the presentation using the q and a widget at the bottom of your console. We will try to answer these during the webcast, but if a fuller answer is needed or we run out of time, it will be answered later via email. Please know we do capture all questions. So to kick off, I’d like to ask each of our speakers to give a quick introduction of themselves and their work. Mike, would you like to go first? Absolutely. Megan, thank you so much for having us today as well. I appreciate everyone’s time and, joining us for this important topic. My name is Mike Worth. I am by title our chief commercial officer of ProviderTrust. I’ve been with the organization for eight years. I have worked in and around health care now for almost thirty years. You can probably tell that by looking at the gray in my goatee, or the lack of hair in my head, Megan. Just excited to be here and have worked very closely, in how we’re helping to solve a lot of the issues with provider data, with my good colleague and friend, Tony three. Thanks, Mike. Tony three, I’ve been, with ProviderTrust now for about five years. I’ve been in health care for about fifteen, so half of Mike’s age. And, I had hair when we first got started. So, excited to be here and, opportunity to talk about, provider data and and some of the challenges we’re seeing. Allison? Yeah. Hi, everyone. I’m Allison, the only one with hair. I’ve been in the health care industry, for ten years now with ProviderTrust for three years, working with clients all over the US. A ProviderTrust specifically, I’ve served as a sales leader to help payers find tailored solutions to help fix some very big problems. Excited to be here. Excellent. Well, I can tell already that this is gonna be a fun discussion with the three of you. Thank you for being here. Just to kick us off, I’m gonna hand it over to Mike to introduce our topic and then over to Tony to talk about the survey intentions and findings. So, Mike, over to you. Yeah. Thank you. And while it is, fun to take a look at these babies, that’ll be presenting today along with the babies akin to the babies with, MPI’s title that we have, Where this comes from is really data that we gathered and have worked with our clients to be able to help navigate and understand, finding practitioners that were born in twenty twenty four, for example. Data is such a foundational element that enables quality work, business processes, and otherwise. And there seems to be a pretty big discrepancy in understanding what is theory and what is reality today. Tony, you wanna talk a little bit about, kind of what we what we try to do here? Yeah. Thanks, Mike. You know, I think originally, we had a hypothesis that we were gonna learn a lot from health care executives, where they were headed, strategically, directionally, and and and maybe even some opportunity for us to to to cherry pick on some of the the survey findings. What was really interesting, I think, as we as we got into this was that there seems to be a really huge chasm between what we got in the survey, and and what our experiences are day to day. You know, specifically, there’s a lot of talk around automation, cleanliness, data that’s available. And what’s interesting there is is as we go through, the findings you’ll see and some of our own experiences, that doesn’t seem to be what we’re what we see, day to day. And so that that chasm of of understanding, by the survey respondents as well as what we see is is where we will dive in and and and look at to to understand where we’re going. Excellent. Thank you. So clearly, there is a lot of optimism out there, and yet we see these insights here on the right that are much less positive. Mike and Allison, can you tell us about where those insights come from? Yeah. Absolutely. So as as Tony was mentioning, we surveyed health care executives. These are from enterprise payer organizations. This wasn’t just like walking around and asking, Joe Schmill off of the street, what do you think about this? So we’re talking about the executives here. And I I wanna make it really clear that there is this is the perception, and then there’s the reality. So the perception here, for example, is the data is verified against the primary source. Now primary sources come in all different shapes and sizes. Many of you who are on the call understand the complexities of navigating that. But when when the the belief is that, oh, no. We absolutely do that. And that is the industry standard and expectation to be able to capture both that tested and verified information. We have found some shocking results in working with clients, now entering nearly two decades of work on this. We we are working with a large payer, and these are all brands, gang, that you would recognize if we would say that. And we don’t and so we’re not doing this to shame. We’re doing it to say, this is the true state. And and the first the first thing is just owning that you have a problem. So so when we’re looking at this data, we’re able to analyze this. One of our clients, ninety two percent of this population with individual practitioners associated with a Medicare plan that they’re administering were on the Medicare opt out list. It it it is it I had our team run this two different times. And then even after I we did it the third, I could not believe that this was actually what was happening in nature. The the how do you run a business if that’s the discrepancy? Right? Now there you also find that the birth years were in twenty twenty four. You find, that somewhere in the eighteen hundreds. There’s another client that we worked with. Just the discrepancy in age, while it is it’s fun fun to be able to, you know, riff on the Internet memes that are out there with the images that we put up earlier, Megan. The reality is is that a very prominent payer organization utilizes and many do some type of a rental network to be able to supplement and enrich their adequacy. We found a practitioner who had passed away. Allison, what what else what else have you been seeing? Yeah. Thanks, Mike. Another part of the survey that that shocked me that we got back was ninety four percent of respondents said that they believe their data is fully accurate and error free. This was really interesting to me because I work with clients every day where I see the exact opposite. We did a proof of concept with a large national payer. Again, one of those names you would instantly recognize. And we found that over nine percent of their par providers had a license issue. So this is a par provider population. These are practicing practitioners that are billing and providing care every day, and these issues were serious. They were things like their license was surrendered or expired or revoked. The types of issues that should tell us that that practitioner should not be practicing or billing, much less be in the par provider network of this national payer. So this really showed us that almost one in ten providers had a critical issue in that par par network. As you can imagine, these kinds of errors are big. They’re concerning for risk, but they’re also concerning in that they result in millions of dollars being lost by the plan. Another client that we did another proof of concept with, we found that over fourteen million dollars in claims were paid out to ineligible providers. That sum also only came from two percent of their total provider population. So that, I think, really goes to show that a even a small amount of bad data, specifically data that’s tied to eligibility, can create massive waste. And, obviously, this directly contradicts what we see provider data leaders saying in this survey. And and part of the the challenge that we also see, Megan, is just the the lack of of connectivity between departments. But there’s this concept, I guess, that, that executives are saying, no. No. It’s connected. And and perhaps but I you know, one of the clients that I work with, shared with me. He said, you know what? We don’t really need to buy like, we already buy this data. We already buy some of this information. But it’s just easier for us to be able to purchase this from different vendors or different point solutions that we have in place. It’s too difficult for us to get it’s not that technically it’s too difficult. It’s that operationally, we can’t get these departments to align, sit down, and work with each other to be able to make this an interoperable or even integrable data environment. We’ve seen some very prominent clients take big strides and big leaps on this. I’m thinking of one in, based in California. They’re doing fantastic work in how they’re thinking about working across teams to be able to solve this problem differently. But, you know, talk about waste and being able to create more efficiency. Certainly, that helps. But the other part of this is that just by saying that it’s connected, well, it doesn’t mean it’s even helpful if it’s connected. There’s there’s, organization that we work with, and often we’ll see this. Hey. We have four million physicians in our, provider networks, right, from all of our different data sources. Everyone knows and by the way, these are not just practitioners. These were physicians. K? So these aren’t just ordering and referring practitioners. These are actual docs. And we know that there aren’t even physically that many of them in the United States. Some of them are have passed away as we learned earlier, but others are just repeated, repeated, repeated or different instances of the same practitioner. The list goes on and on and on. The difference between the two perspectives that you’re sharing here is really remarkable. So, Mike, what do payer clients say when you show them the discrepancies? Well, I so so, it’s easy for us to sit in this position and and look at the data that we have. The reality is is that we do partner very closely with a lot of these organizations. And, I’ve got a lot of friends now, not just call not just just associate, but friends that are, running provider networks that are instrumental in working on credentialing, that are fantastic people, who are doing great work. And if I was in their shoes and I heard kind of our introduction here, I might be a little bit defensive at this point. And the reality is is that I think that there’s a few things that happened. One is that, the industry, until very recently, great thankfully, very recently, but until very recently has has really been an antiquated model of what credentialing and really behind credentialing, what what effective data management should be. It’s antiquated. It was moving a manila folder from one person’s desk to the other and putting the routing for signatures on top of that. And then what happened is that you had these organizations that would build out software and and other platforms that, that look slick, that were that were fun to be able to see, that tried to enable that process. So instead of taking it from the desk and moving it over, I just routed it for you to be able to digitally sign that. Certainly, there’s some benefit to that, but the underpinnings of the problem are not the process. It’s the data inside of that. I don’t care how slick or fun your UI is, or that experience that you have as a as an individual can be inside of some application. But the reality is is that it’s the data behind it is a huge part of the process that then we could enable our people to be able to work on much more effectively. So, you know, it’s the the credentialing team, I think, is dealing with a lot of the kind of expectations that were set in the industry. I think that, another part of this is that there is a lot of false promise that’s out there. I’m I I mentioned slick and bells and whistles a little bit. I will tell you that some of our most of the clients that we get have actually tried something else first because there’s a lot of money that is poured into marketing. All of these promises of this platform will work or we will solve this problem, it works great in a demo. But when you actually start to be able to say, how do I show up six months later partnering with an organization, digging in and trying to figure out after they’ve made five acquisitions over the last decade, this combination of data sources, how do we unbundle that and actually utilize that to be able to drive and power our business processes? It’s around credentialing, around making sure that our directories are accurate and effective. Like, these are the things that organizations have the opportunity now to be able to do. But sifting through that noise is really difficult while we also during the day have to keep the lights on. So, you know and and part of me is just I I I think that there’s a little bit of an ivory tower issue here. Right? And I’m not talking about the folks who are really trying to drive change. I’m talking about some of the folks who are sitting and looking at spreadsheets inside of these payer organizations. They’re saying, well, we spend a lot of money. Well, we bought this other thing two years ago. Well, it’s supposed to do all this stuff. And there’s really this disconnection from understanding not just that it doesn’t work properly, but what is the actual economic business issue that this is creating for us? And that’s there there’s just some level of oblivion to that. So I think there’s a lot of great people on the front lines of this who intimately understand this problem. And being able to to get that connected into why do we need to make change as a payer, I think that’s the opportunity that’s sitting right in front of all of us. So how do we get from the confidence then that we see in the survey to brass tacks challenges you all are experiencing with your clients? Where does that disconnect come from? Well, I I mentioned earlier that there was, this kind of, you know, the the heritage of of the industry. Really, if you if you go back and look at where did credentialing start, you know, we are, certified as a CBO by NCQA. NCQA, I think, has done a fantastic job of, raising the bar and saying, let’s look at this differently. So if you if you look at how credential was set up originally, it was that every three years, we would take a look, an intense look at a practitioner’s profile. You know, some organizations, two years. But part of the the the difficulty with all of that was trying to amalgamate all of the different sets of information to be able to review and to do that at a scale that was even humanly capable. Right? And we were literally talking about looking up folders and such. And NCQ, I think, has done a great job of that by saying, no. Once every three years is not good enough. There’s been this ongoing kind of monitoring component, but they’ve expanded what that remit is. They’ve gone significant on saying we have to be able to understand was there a board action against this practitioner. Are we managing and tracking expirals expirables around this practitioner? Are we looking at the state Medicaid exclusion list? By the way, fifty states, District of Columbia, that’s fifty one total that should be in existence that came out with the two thousand eight Affordable Care Act. There’s only forty three of them that are even accessible by anyone because eight of those locations haven’t even made that available. If you wanna know what those are, please follow-up with us after the show. So, like, there’s there’s all of this that has to happen. That is that standard had to get raised. That’s the first part of it’s really saying that that that this this is not good enough and that things need to change. We don’t need to be able to just take the Manila folder, put it online, and move it from station to station. Data can drive how we make decisions, and that can free people up to be able to focus on the most critical aspects of practitioner care, of of really creating a far better member experience and reducing cost inside of these organizations. The opportunity is right in front of us to be able to take that, and I think it’s gonna take some individuals who are in these in in the payer organizations that are willing to make the change, to be able to make that happen. But I tell you what, change happens when the pain of doing something different is less than the pain of doing the same thing over and over again. And we’re seeing enough of this problem today that is really starting to separate the haves and the have nots in these pair organizations. Enrollments that are taking ninety days, a hundred and eighty days versus organizations that can get an initial enrollment down to seventeen days, fifteen days, eleven days. Like, this massive chasm, that’s what’s gonna separate the haves and the have nots, and that’s just one little slice of what’s gonna change. And that positive change is gonna push all tides across. Excellent points, Mike. Thank you so much. What would you say is the risk of this overconfidence as you call it? What’s at stake here? How does it affect health plans, providers, and members? Yeah. I so so, you know, I I think part of it is just starting with the member experience. I have health insurance. I hope, Megan, you have health insurance. Right? All of these individuals, that we’re trying to take care of in our country to be able to provide access to care, there’s a payer behind that person. And creating an approved member experience is a big part of what’s gonna separate organizations in this regard. If you can separate away from that a little bit and think about the members that are going through this, as I go in and try to find a practitioner and do you accept my coverage, that is something that the payer, my my my servicer, right, of my access to health care is supposed to be able to deliver for me. Those directories are the backbone of me being able to go in and access that. And the reality is is that there there are errors all over the place and inaccuracies. Now it’s not just the payer’s fault on this, and and I think this is part of what we’ve gotta be able to own. For example, in order to be able to, you know, negotiate my contract as a as a practitioner, I’ve gotta be able to kind of set some terms. Some of them may be or I may indicate that I’m gonna take, Medicaid patients or even Medicare patients. And I’ve seen this firsthand where a Blue Cross of, insert, I’m not gonna tell you which one, made a phone call from Blue Cross doing audit checks on their directory to be able to find out, do you take right? Are you accepting Medicaid patients? Very next move or sorry. Medicare patients, I said. Okay. Medicare patients. The very next move, ten minutes later, called the exact same place from inside the same building using a cell phone, personal cell phone, asking the same question and got two different answers from the same office. Right? So part of this is that this is just acknowledging that all of this stuff is happening and that data is central to to being able to help drive and power these decisions. But I think it’s the member experience. I think it’s it’s the practitioner experience. There is always gonna be healthy tension between the payer and the provider. You have these payvider organizations that even experiences inside of the four walls of their organization. But but I think this this kind of juxtaposition of embracing it to be a healthy tension, not one that is adversarial, And changing that game is gonna and make it easier for practitioners to be able to be involved in the the the plans that that really need them to be able to demonstrate their access and and and adequacy across the country. So I think that’s gonna that’s gonna drive and change behavior as well. And if nothing that I said hugs at you emotionally or morally, then let’s just stick with this mister and missus payer executive that we’re trying to talk to here today. You’re losing money by not dealing with this, and the financial impacts of this are gonna separate the haves and the have nots. So that that’s kinda what I think is gonna be the the impetus behind how a lot of these things happen. The reality is is that if we’re running a business and we keep the member and the practitioner as key stakeholders in this equation, I think that you’ll see efficiency driven out of this that will drive a a far better, experience, able to be delivered by these payers. Such good insights, Mike. Thank you so much. So, Tony, let’s go over to you now. I wanna pick apart some of these survey insights because I’m wondering if some of this boils down to a difference in definition. For example, ninety two percent of respondents said their data was clean and easy to understand. What does clean data actually look like? Yeah, Megan. That’s a that’s a great question. And I think something we really should define, I think, is where we sit in this, in this space. Really clean data is is going back to the the primary source. Right? We see so often that, as we sit in that middle between a payer, a a specific license verification, or a provider type, that that we need a bit of a a Rosetta Stone to understand all of the different permutations of a provider. And really what I think what we believe is that, the the data should be clean as it relates to the primary source. So as you’re talking about a a cardiologist, right, that they have specific, board certifications that require specific values, specific codes, essentially, as well as their their license at the primary source may have a certain statement to it, around it. Oftentimes, what we would see in that in that certain scenario, maybe they call everybody a medical doctor. Right? Or often we call everybody a dentist. When in reality, there are certain things about that provider, that provider type, their their credentials that is more specific, and it and it allows us to then once with we have that clean data, data, once we we say that this is where we’re going to to go and grab our information from, it then allows us to, to really bring about, specific provider provider requirements that allows us to move, move the industry. Right? Really, clean data isn’t just about getting clean data. Obviously, we wanna have, the easiest way to work with, data as it flows through the system, but it’s really that data then driving decisions, that allow the, organizations to to continue to understand their provider accuracy, their provider, availability across their network. And having those those bits of information, as accurate, as clean, a golden record, if you will, helps us help helps us all as we’re moving through, health care. Great. Thank you, Tony. And a similar question then for data automation. Across the board, roughly eight in ten people said many provider data management activities were entirely or mostly automated. What does data automation look like truly? Well, I I really wish we had followed up with a question on that one, because I I do wonder what they mean by automation. Well, I I this is where I wanna define automation. Right? Just because you have technology doesn’t mean you have automation. And Mike mentioned earlier, right, the the Manila folder. Right? Taking a Manila folder, digitizing it. Right? Like, we use like, we did in the early two thousands with electronic records and then working them through the system doesn’t mean it’s automated. And so that’s that’s really question I I wish we had like I said, I wish we had followed up because, you know, when we think of automation, you know, it really starts at the beginning. It starts with that clean data. Right? Assimilating, collecting the data, understanding the data, synthesizing the data, bringing it all together. Right? We we talk about the fact that organizations have multiple systems. So the fact that some organization may have four million providers will you know, again, they probably have, a a technology solution, maybe multiple technology solutions. But if you end up with four million providers, did you really do the work around ensuring that there’s one provider across four systems? Right? And so when we think about automation again, it’s that collecting, it’s the assimilating, and then ultimately taking all of that data and putting it where it needs to be put inside of the organization to drive decisions. You know, if you think about a lot of the word, you know, words around AI, like, that’s really what we’re trying to talk about here is and and AI is a is a buzzword, but, you know, really, it’s about that, that working it through the system and not just repeating, old, practices with technology. And what about data centralization? I understand that eighty one percent of people said their data was centralized, which seems very challenging to do given all the different departments that need access to this data and all the different types of data sources too. So what is data centralization really? Yeah. That’s that’s another another question that I’d have about this survey. You know, because data centralization as as we’ve seen it, isn’t isn’t necessarily happening. Right? In health care, specifically around provider networks. Right? I I would say, and I think we’ve all said that it’s it’s not as, mature as maybe an HRIS system, an HR system. And so, you know, in this case, right, what we have is a solution around claims management. We have a solution around our provider management. We have a solution around our, provider network. And and maybe they’re connected. Hopefully, they are. A lot of times, we find they’re not connected. And so, again, you end up with a record of of of Tony here, Anthony here, you know, T here, right, across these organizations. And so really data centralization, as we as we view it, as we as we want to design it, is essentially that that central central location. And all of the other downstream systems, whether it’s claims or or the provider directory or other systems, all come off of the central, again, clean data that’s been synthesized and automated and brought into the system so that we understand, not just, you know, first name and last name, but but we have oftentimes where a provider started in the in the industry, you know, under their, under their under their first name. Right? But then they got married, and so now they have a different last name. Right? And so we need to be able to collect all that information to understand the full breadth of that of that provider. And, again, once you have all those permutations of just names as an example or or addresses. Right? I worked at when I first started, I worked over here at one two three Main Street. Maybe I moved to a different location. Can we wanna collect all of that in one space so we have that information? And then we can drive decisions throughout health care, throughout the payer, based off of the bits of information. It doesn’t mean that you have to use all of the information, but at least we have that catalog of who that provider is that is allowing us to make, further decisions down the street downstream. And, Megan, to Tony’s point, that takes an executive in the payer organization that has vision that can see that these teams can work together differently, and we have clients that are absolutely doing that today, that are that are walking with that vision. But that’s what it takes out of the folks in those seats. The folks that are the oftentimes tasked with running the point solutions are some of the ones who are saying, it would be better if we need to be able to have these work together. But the lack of that coordinated leadership is really what the challenge is. Frontline team members and credentialing see it because they know that if we had it here, this would actually solve some of our directory issues over here. We hear this constantly from our clients. It’s getting to this point and not letting the executives get away with just a bunch of folks who fly in, who show fancy types of, you know, slick interfaces on for for data ingest that’s a prepackaged demo that actually can say, let’s talk about how data can transform your organization. Let’s have a vision for how that’s gonna work because the reality is is that’s just really hard to do. Think about taking the federal interstate system and state highway system and making all that work together. That’s real work. That’s what we’re talking about doing is making all of those things work together. But that’s a city. That’s a state. That’s the federal government that you have to get an alignment around this. What we’re talking about is not that far off from being that complex. Probably even as regulated too. Thank you so much. Tony, I’ve got one more question for you before we turn to Allison. What are some signs that payers have an undetected problem with their provider data management? Like, what are some red flags that could indicate things aren’t as rosy as they seem? That’s a great question, Megan. I I think it really comes down to about three or four things. Really, it’s it’s timeliness of data. So we know that there are, as as Mike said, right, NCQA is asking for monthly checks on a variety of new items. Sometimes, we’ve seen that, data, from the primary source where you’re trying to check an exclusion list, say, from a state sanction all the way up to the federal government. We we see that there’s time gaps in between there. Right? So if you’re only checking one list, if you’re only checking the federal list, you’re not checking your state Medicaid list, there there are gaps in those times. So it’s it’s how often do you check it. Accuracy. Right? Again, it’s it’s gonna be hard on a large provider network to ensure that we understand that a provider is not born in twenty twenty four. Right? It’s very easy to make those, typographic changes and and errors, but we but we need to make sure that the data is accurate. Right? And we need to do consistent checks on our provider data to ensure that it has the right information. We’ve already talked about, you know, ensuring names are correct and addresses are correct. I mean, those are those are two, big ones. But but having that, having that data accurate as possible is key. And then, again, with redundancy, right, if we have multiple point to point solutions, they all have the same data in them, they all have different databases, but they’re they’re using the same data. How how can we bring those together? Right? To Mike’s to to Mike’s point, how do we, have a holistic approach to what data means and being able to use that across the organization? That, you know, already spoke to the point to point solution, so that’s so that’s, already covered. And then I think, you know, Mike mentioned earlier as well, you know, one of the things that we’re seeing is really just, potentially, you know, maybe adversarial somewhat adversarial relationships between, you know, provider data providers to where the data needs to go. And I and I think, you know, it goes back to to what Mike said as well, which is, you know, we really have to put two people at the at the center. It’s it’s, of course, patients. That’s the point of health care is to serve patients, but it’s also the provider. And if we’re asking a provider to fill out the same application for four different plans and use the same information, You know, what’s what’s surprising to me is in in health care when we credential each organization, whether it’s the the health system themselves or each of the individual payers that are providers part of, all of them are doing the same credentialing work. And and oftentimes, it’s the same data being sent back and forth. So, again, if we can get to that data centralization, if we can if we can bring people back into, into that the narrative of the data, I think that those are all the things that we’d wanna look at. And if if you’re having issues with that in your in your organization, any of those issues, again, the opportunity to stop and, and have a conversation about a holistic plan moving forward. Excellent. Thank you, Tony. So we have talked about the challenges. Now, Allison, let’s talk about solutions with you. I suspect a big part of that conversation is in who you engage for this. The Studio ID survey found that eighty six percent of people said they were already engaged with a vendor for their provider data management, and the vast majority of them are happy with those relationships. So how can payers be more selective as they consider who they’re contracting with for provider data? Yeah. So I would like to start with that point. The survey saying that eighty six percent of people are happy with their current vendor. That’s pretty wild considering all the problems that remain in this space as we’ve covered from Mike’s point of view, from Tony’s point of view. You would think if these vendors are truly doing good work, these problems wouldn’t exist. So we obviously know this provider data issue is large. It’s by no means new, and neither are a lot of these vendors or solutions out there in the market. So I think this this kinda goes back to, is it true satisfaction? Other options out there. There are newer things, better There are newer things, better options that can help with these problems that I think a lot of these payer executives may not be aware of. Previously, there have not been better options. So, of course, you’re gonna be happy with what you had because you didn’t know any better. For a lot of clients that I work with, I really have seen that reevaluating this process has taken a new team coming in a top down company wide initiative to push them to take a step back and say, okay, maybe we should reevaluate the way that we’re handling credentialing, the way that we’re handling our provided data processes. Oftentimes, like I said, I don’t I don’t think these organizations even know that they have a problem until they’re forced to reevaluate it. And they assume that they’re just checking a box and can kind of wash their hands of it. I would imagine that payer executives would, and in my opinion, frankly, should want to know what other solutions are out there to improve provider data accuracy. Sorry. I was gonna make one more point. I think payers are doing the best they can. I think we’ve hit on this. Some some people within payers are doing the best we can. I think we’ve hit on this, at several different points throughout this this this conversation, but there’s a lot going on in this space. There’s regulatory issues that are ever changing. They are being told to grow their network size with tougher restrictions on budget. And there are vendors out there that are saying they can solve all of these things at once. And I think, a difference in how we look at things at provider trust is that we are confident in our ability to solve our piece of the pie, and we don’t claim to solve it all. So I think that’s that’s where we stand out when it comes to other vendors in this space. Perfect. Thank you so much. That’s good insight. Okay, Allison. One last question for you before we jump into audience questions. If payers do nothing else after seeing this webinar, what’s the most important thing they should do? Yeah. That’s a great question. So I would say go talk to the people that are in the trenches. I think Mike hinted at this a little bit. Executives, I really believe, need to go down one level and have direct conversations with the people that are doing this work every clearly, by these survey results, they aren’t getting it. We see the results from the proof of concepts we’re doing from spending time with these clients every day. So I would really encourage those executives to go ask your head of credentialing, how long does it take a provider to be become fully credentialed? Do you have a a backlog? How big is that backlog? Go ask your compliance lead. How confident are you really that your provider network is risk free? Do you have any doubts about your monitoring vendor or process? Go ask your team managing the provider directory. What are your biggest frustrations? What tools do you wish you had to make, the directory for members more accurate? I think leaders just really need to start asking the people that are working with this day to day what’s actually going on because, obviously, we’re seeing a big discrepancy in how they look at things and how things really are in reality. There is a lot of risk and waste here, and I think starting a conversation around this is the least that these executives can do. So, Allison, one question before we move on. What is provider trust doing to help solve these challenges that we’ve been discussing? Yeah. Great question, Megan. So last year, provider trust launched a new solution called DynamicNPI. This is a solution that we are extremely excited about and proud of. It works to return verified provider data, including results such as sanctions, license issues, exclusions, PSBs, and other data points that are key to determining a provider’s eligibility. So it goes right along with this conversation we’ve been having today. Also, it returns all of this data instantly with only an NPI, and it can fit seamlessly into credentialing workflows. I really see this solution being a game changer in this space. Like we’ve talked about today, for too long, the solutions that have been offered have been stale, they’re too similar, and they’re clearly not making a positive impact. I’m really excited to be working at a company that values innovation and is bringing something new to this market I mean, imagine what the client examples that we talked about earlier would look like if they had access to a solution like this. I see this, and I know it will save organizations tens of millions of dollars in waste. It’ll allow organizations to be one hundred percent confident in their provider data and its accuracy, and they can literally instantly eliminate their credentialing backlog. All of those are just a few examples of the impacts they could have. It’s really exciting. Excellent. Thank you all so much for this great discussion. We do have some time left, so I’d love to shift to some questions from the audience. We’ll start with this one. I’m not ready to do a total cred overhaul. Can I use dynamic NPI alongside my CVO? I’ll take that one. That is a great question and one that we hear frequently. I would say yes. Absolutely. The majority of the clients that I’m working with currently that are implementing our new solution, dynamic NPI, are in the same exact spot. So they’re happy with some part of their process. They are ready to do a total overhaul, which is completely understandable. Something like that takes years of planning, takes millions of dollars potentially that you may not have in your budget. But the beauty of Dynamic MPI and the way that we work at ProviderTrust is that we don’t believe in an all or nothing solution. You can plug us in to your overall credentialing process to quickly and easily bring some quick wins, some efficiencies. For instance, one client I’m working with, they don’t have a process yet or did not have a process yet around the ongoing license tracking that NCQA is requiring going live on July first. Dynamic MPI, our solution is to solve for that. So they’re they’re keeping their CVO. They’re keeping their standard credentialing process, but we’re plugging in for that one thing. So I think we really wanna meet you where you are and help you get some quick wins, and I believe that’s what our solution does. Excellent. Thank you so much. Our next question asks, I already know my team has a data problem. How do you convince the executives to change course when they won’t admit there’s a problem? I guess, we talk we’re talking about a data intervention here, I guess, Megan. I think one of the things that we, that we we would encourage y’all to do, is I mean, frankly, you can call us. One of the things that we do with our clients is pretty simple. We take their data. We’ll bump it up against what we know. Allison was talking earlier about, you know, some of the changes that are happening with the in, NCQA requirements. And, I got a call from someone. They said, would but but these state Medicaid exclusion lists, like, have you ever looked at these? I’m like, yes. Yes. We’ve been looking at these for for over a decade now. And but but they don’t have any unique identifiers on them. Like, yeah. Some of them, that’s absolutely accurate. It’s a name, first and last, and an address. And it’s a PDF document, and it shows up very regularly. And sometimes it has six months of backdated information that’s on there. Yeah. It’s really different. That state does it that way. Other states, much more effective in how they administer it. So point being is that we’ve taken all of that, can take client information, client data, bump it up against what we know, and we just do that for organizations who are exploring a potential partnership with us. We look at this for the long term. Right? This is not no data effort is a point in time fix. There’s no such thing as a data project that solves all of your problems. You do a data project to then enable ongoing, not just accuracy, but high hygiene. Right? And then that enables relevance to what you’re trying to solve for. So that’s one of the things that we look at. I think just showing that there are now standards and that there are fines and penalties and potential repercussions to organization hitting us. You know, Allison mentioned that we’re we’re able to do the ongoing board action monitoring, But you start scratching at this and say, okay. You wanna get help. Just make sure that you are also doing your diligence and asking the right questions of vendors that are out there because the way that we do it is very different than the way that somebody else does it. We’re able to provide you with the actual board action information, the screenshot of that information. We’re able to to extrapolate the data from that and then make it operational inside of your data and work or or or or in inside of your workflows, powering it with that that information that’s there so that you can get individuals who are working in credentialing credentialing or otherware to be able to take action on that and do the hard work that requires human hands to be able to manage it. Those are those are just a couple of things that I think about. But, overall, you know, I I think that the the the last way is just saying, you you better you better drive this change, in in unless you want change to come happen to you because change is coming one way or the other. So that’s the conversation that I would try to have with those executives. If you like the point of view that I take on this call, you can call me. If you’d prefer to have Allison, if you think she’d work better or Tony, you can call you can call on that. So there you go. There’s a little bit of a, hopefully, help helpful guidance for you. Excellent. Thanks, Mike. I think we’ve got time for one more question, and that is how does AI play a role in this? Yeah. I’ll I’ll take that one, Megan. I I think, you know, look, a AI is the buzzword of the day. You can’t, go to any social media platform today and not see somebody talking about how they’re using AI. But but I think it goes back to what we we tried to stress here in this conversation. You know, it it starts with the data. Right? I mean, you can take any, process you have and try to digitize it. We’ve already mentioned, right, taking from Manila, folders of of chart records and then digitizing them. Was it really a a change in in in in transformation, or did we just really digitize what we were using in those Manila folders? We’re talking about AI today, but, you know, ten years ago, we were talking about automation, which what that really meant was adding in technology, adding in a platform. Again, now we have all these point to point solutions we’ve talked about. So, again, is that is that IAIs and automation? Or do we have these these platforms that are storing the data that has issues and we’re just continuing on with our our current process? So I, you know, I think it we have to start with the data. We have to understand what it is we’re trying to really do. And when we mean AI, what are we what are we really talking about? And so can AI help? Sure. It can. But I think you really have to design that process. I think something we’re doing at provider trust is really thinking about, again, the holistic provider journey. Thinking about how we get that data, how we collect it, how we synthesize it, how we bring it back in, and and take that data and put it into the places and in the hands of the folks who need to use it to make decisions. So is that AI? I don’t know. But it is at least, using the technology that’s available to us to, to really make a change in health care. Excellent. Thank you so much. Before we wrap up today, Mike, any final thoughts that you’d like to share? Yeah. Thanks, Megan. I I was talking with a good friend of mine last night. He’s the CEO of a software company, and, we’ve known each other for a long time. And we were talking about you know, I mentioned earlier we mentioned beginning, I’m old. And, one of the things that when I got started in in this world, there’s a lot of talk about quality, about, there’s the hundred thousand lives campaign that Don Berwick had spearheaded, but crossing the quality chasm crossing the quality chasm, six sigma, TQM. Like, all of these things were were drivers, not just in health care, but in business overall. And that seems to have waned. You don’t hear that in the same way anymore. And and we were discussing this. And one of the things that that he and I were were talking about was, was like, okay. But if you get some if you build software, if you get it out there and you can iterate on that and make improvements on it, doesn’t that eliminate for some of the need need for quality? And I said, I I don’t know that I totally agree with that, but I will say that that if if I equated software and data, to to plumbing in a house. Right? So we’re gonna use the plumbing, the infrastructure, the pipes, and we’re gonna use water as the data that flows through it. If I said to you, Megan, you know, that we’ve got ninety five percent of it is right, inside of your house with the plumbing, now there might be some leaks here and there, with the water, but but overall, it’s ninety five percent accurate. I don’t think you would be okay with that. And and I think that’s that’s where I start to kind of look at at this this mindset around data versus other operational processes that can be refined and improved, there there’s a level of this that says you know, go back to the banking example. In your bank account, would you be okay if it was ninety five percent accurate every month, but you didn’t know what was changing and you couldn’t identify unless you really dug into it? That seems wasteful to me. That doesn’t seem like a way to manage this more effectively. So while it’s cute for us to be able to talk about, a baby with an NPI, the the acute part of this is that we have seen organizations, payers that have been fleeced for fraud and waste by by a spouse of a past practitioner, somebody who did was deceased, but was still actively billing underneath their their NPI for over a year. That’s you’re never seeing those dollars again. I I talked about the the, the supplemental network issues that we’ve seen. This happens time and time and time again. And and when you think about credentialing or you think about directories, and, really, we’re thinking about just a fundamental business problem. If we think about it as the three legs of the stool that says we’ve got to have the right processes, and we can use and optimize technology to enable those work processes. Inside of that, if we have optimized our data, we can Inside of that, if we have optimized our data and then freed up practitioners, the folks who are in credentialing, the folks who are working in directory, these provider network teams that are so often the unsung heroes of trying to solve and make this work better, if we listen to what that is and really paid attention to the data, the platform, and the process and thought about them independently, we could actually create a far superior experience for practitioners that are in our networks. And, absolutely, it would translate to the families and the members that we’re trying to take care of as well. So that’s our point of view here and really appreciate the time for us, being able to be with you in the audience. Well said, Mike. Thank you so much. And that’s a perfect place to end our discussion today. This has been wonderful. I’d like to thank our speakers, Mike, Tony, and Allison, for a great discussion today. We appreciate you sharing your insights and expertise with us. And I’d also like to thank our audience for joining us today. We hope to see you again soon. Have a great day.