Key takeaways
- Market consolidation & organic expansion: While M&A activity in urgent care has slowed, leading operators are still driving growth organically through expansions.
- Evolving reimbursement pressures: Flat net revenue collection and CMS fee adjustments are squeezing operational margins, forcing practices to seek efficiency elsewhere.
- Automated payer scrutiny: Payers are leveraging AI and automated algorithms for large-scale claim downcoding and denials, making manual review insufficient.
- Increased regulatory oversight: Federal agencies are utilizing data and AI analytics to identify billing anomalies across provider organizations of all sizes.
- Shift to midcycle AI solutions: Revenue cycle management is shifting focus from reactive back-end appeal battles to pre-billing, midcycle documentation and coding accuracy.
Introduction: five forces shaping urgent care
Adam Morris: Hello and welcome, and thanks for joining this webinar on the five forces shaping urgent care in 2026. I'm Adam Morris from Charta Health. Charta Health builds customized AI chart review for provider organizations across specialties to analyze every clinical encounter note across clinical dimensions, including coding accuracy, documentation integrity, payer-specific compliance, and clinical quality measures. I'm joined today by my colleagues, Jake Sandler and Guy Bergman, who together have years of experience serving the urgent care market and collectively have spoken to dozens of leaders of urgent care organizations in just the last couple of months. I'll pass it over to Jake and Guy to introduce themselves. Jake, let's start with you.
Jake Sandler: Hey, everyone. Really happy to be here. I'm Jake, one of the growth leads here at Charta. Been here for about a year. Prior to Charta, my background is a little bit more in the behavioral health side. I worked at a large behavioral health MSO where we were seeing over 500,000 patients a month. That's really where I saw how broken RCM and billing and coding and all these things could be. And so about a year ago, I joined Charta. I got my CPC to dive into the coding and billing world and have been working really closely with our urgent care customers the last year and change.
Adam: Guy?
Guy Bergman: Thanks, Adam. Hey, everyone. Guy Bergman. Really excited to be here. Been in healthcare tech now for about ten years, with the last six or seven years focused specifically on rev cycle. Most recently, I spent several years at Experity, which I'm sure many of you are familiar with, working closely with urgent care organizations all across the country. Over the years, I've had a chance to speak with a lot of urgent care operators about everything from growth, staffing, and reimbursement. So super excited to be part of this conversation today and share some of what we're seeing in the market.
1. Macroeconomic headwinds and competitive shifts in urgent care
Adam: Alright. Thanks. I'll be moderating today's webinar, and I'll be asking Jake and Guy to give some more dimension to some of the facts and figures you'll see on the screen, which will give some cold, hard data to the forces driving the changes in urgent care that we'll be discussing today. We'll look at each of these forces individually and pause after each of them to hear from Jake and Guy about how urgent care leaders are responding to them. Okay. Let's get into it. The first of the five forces shaping urgent care is this shifting terrain in the competitive landscape. We're seeing some big shifts in urgent care competition. Some of these are long-term trends. Others are more sudden. For one thing, and this has obviously made big headlines, there's the ongoing rise in the uninsured population. Now that the ACA subsidies are gone, a lot of people are foregoing health insurance. The original projections from the Congressional Budget Office in 2023 on the subsidy lapse estimated that about 2,200,000 people would leave the exchange, but the impacts have actually been a lot worse than expected. The latest projections from the Kaiser Family Foundation estimate that enrollment could drop to 17.5 million in 2026, down from 22,300,000 in 2025. That's a drop of 4,800,000 people. And the hardest-hit states are going to be in the South, places like Tennessee, Mississippi, and South Carolina. Now you might take a step back and think, well, this could be a positive thing for urgent care clinics. When someone loses coverage, they might be a lot more likely to walk into the closest urgent care clinic than their former primary care provider or an emergency room. And that's probably true to some extent, but the negative consequences here most likely outweigh any potential gains. Urgent care teams will see more problems collecting payment and probably see a rise in uncompensated care. Meanwhile, competition between urgent care businesses themselves is higher than it was a decade ago, with the number of clinics doubling between 2014 and 2023, buoyed, of course, by that surge around 2020 related to the COVID-19 pandemic. Now private equity leaders have already priced these headwinds into their deal-making strategies. M&A activity in urgent care was down nearly 40% in 2024 relative to 2021 when there was still a lot of enthusiasm. So, Jake, let's start with you. Tell me how this is showing up in your conversations with urgent care leaders.
M&A dealmaking in urgent care slumps
Jake: So the deal-making slowdown is definitely real, but I think to your point and the interesting part is even with M&A down, the groups that are healthy aren't sitting still. They're growing organically instead of through acquisition. They're opening up their own locations. And I'm hearing this everywhere. I spoke with a group that has about 80 locations that told me that they're planning to double their footprint over the next two to three years, all de novo, all greenfield builds. Another group I spoke to has 55 locations. They've already signed, I think, six or seven leases this year, and they're eyeing 20 more for next year. And one of the largest urgent care operators in the country told me that they're targeting somewhere north of 150, even 175 new locations over the next couple years. And so I think the picture's a little counterintuitive. We'll get into this more. Margins are obviously thin, and I think a lot of groups are genuinely struggling right now. But the winners, especially the big, well-capitalized groups, are using the momentum to expand aggressively and grab share. They're not waiting to buy their way in; they're building. And so I think even with M&A down, the ground is actually heating up. There's more competition in the space, and the strong are getting stronger. That's typically what I'm seeing across the market.
2. Declining reimbursement rates and margin pressures
Adam: Thanks for that. And you mentioned margins. So that takes us to the next force, which is about some of the more direct economic headwinds facing urgent care teams. So the TL;DR on this slide is easy to see in the chart here. Direct margin pressures have been going up for urgent care teams. And I know a lot of you have been feeling that every day. So let's dig into the reasons why. The first is that reimbursements simply haven't kept pace with the cost of running an urgent care clinic. And the primary driver there is CMS's physician fee schedule, which sets the baseline for what providers can expect to be paid as reimbursement for services from payers. For example, in 2024, CMS decreased calendar year 2025 reimbursements by 2.83%, which cut reimbursement by almost $2,000,000,000 in the US. Now where CMS goes, private payers go too. They use those CMS figures as a baseline. So typically, if CMS isn't doing an increase, neither is any of the commercial payers. Now CMS actually raised the fee schedule for calendar year 2026, but it also created a new efficiency adjustment. That's a 2.5% reduction that applies to more than 7,700 CPT codes. And the result for the affected codes is a net increase of less than 1%. Now, fortunately, E&M codes were excluded from that efficiency adjustment, but it pretty much affected every other commonly billed code in urgent care. So it's a little bit of a mixed bag this year. CMS also decreased the fee schedule in just 10 of the last twenty-five years. So you might think, okay, 15 out of twenty-five years, you're winning more often than you're not. But that's not really true either. The more concrete way to think about this is relative to the cost of doing business. So when CMS does these increases, they're usually not keeping pace with inflation, let alone keeping pace with the inflating costs of operating a practice, which have been increasing faster. So if you've been in the business longer than a few years, you've probably already felt that slide. So now, Guy, I want to turn to you on this one. How is this downward pressure on reimbursement affecting the urgent care operators you're talking to?
Net revenue collection in urgent care is stagnant
Guy: Yep. It's a good question. So I honestly hear about it all the time. I was just having a conversation yesterday with an operator, the CEO of a 13-location practice. Staffing costs have increased. Technology costs have increased. Just about every operating expense has increased for him, but the amount of revenue generated from the average patient visit really hasn't changed all that much. And there's published data on this, right? Net revenue collection per visit has pretty much remained flat since 2020, genuinely hovering state by state between $120 and $130, and that's the squeeze operators are feeling. The revenue just is not keeping up with the cost. In fact, according to the AMA, when you adjust for inflation and the cost of operating a practice, physician reimbursement is down about 33% since 2001. I think most operators on this webinar probably don't need a chart to tell them that. You've lived it. Many urgent care groups today are seeing more patients, working harder than ever, and still feeling margin pressures because the economics have shifted underneath them. The important thing is most of these pressures are happening completely outside of their control. You're not going to negotiate your rate out of a CMS reimbursement cut. You're probably not going to wake up tomorrow and see staffing costs suddenly fall. So when organizations start looking for ways to protect margin, they honestly have to look elsewhere. They have to look at operational efficiency, revenue cycle performance, coding accuracy, denial prevention, and all of the areas where revenue can be impacted before a claim is ever paid.
3. AI-driven payer scrutiny and automated claim denials
Adam: It's definitely a tough environment. But let's move on now to the next of the forces, which is payer scrutiny. So you both told me this, that payer scrutiny is one of the most discussed subjects of the past year when you go out and talk to operators in urgent care. And I think everybody listening on this webinar probably has some battle scars related to the rising tide of denials. A lot of folks are wondering what to do about it. But before we get to the what, let's first look at the why this is happening. First of all, practically every insurance plan in the country is already using AI or is actively in the process of implementing it. And, obviously, one of the things they're using AI to do is scrutinize claims data. One of the payers that's been out in front on all of this is Cigna. And a lot of what we know about how the payers are adopting AI comes from the publicity and the disclosures around some of the things that Cigna's been doing. So, famously, Cigna rolled out an auto downcoding policy last year, and it was pretty unpopular. So after strong industry pushback from advocacy organizations and a $500,000 slap on the wrist from the California Department of Managed Health Care, they agreed to pause that policy temporarily. Separately, Cigna is also defending a separate but related class action lawsuit in US District Court here in California. The suit was brought by a class of plaintiffs who alleged that Cigna was using an algorithm to deny claims at scale with improper review. Now these denials actually came with a letter signed by a physician, but the lawsuit claims that one of the physicians, so just one working for Cigna, generated about 60,000 denial letters in a single month.
But it's not just Cigna, of course. Tech advances are enabling all the payers to review claims at scale in ways they just couldn't do before. According to the Kaiser Family Foundation, about 20%, so one in five in network claims made to ACA plans got denied last year. That is a huge drain on provider resources. And one of the things that payers are doing here is, you know, they'll auto deny the claims with algorithms or kick back a medical records request and then use AI to scrutinize documentation at scale to find new reasons to deny the claim. And concern over how this is going is not confined to the revenue cycle office. Right? So six in ten doctors are actually worried not just about what this is doing to the cost of care, but what it's doing to the quality of care too. So we'll turn back to you on this one, Jake. Tell us what you've heard about how payer eye AI is showing up in the urgent care rev cycle.
Jake: I think this is one of the biggest themes that operators keep coming back to, and it's payer downcoding, payer denials, and how the AI on the other side has completely changed the game. One of my favorite stories actually, I heard from one of our customer calls that a C-level executive at Cigna actually let it slip that their system auto-downcodes all level fours that don't have a second diagnosis code. So, basically, adding a second diagnosis code to a claim would override their automated downcoding. And so I think it's really wild how blunt these systems can be. And, obviously, they don't have the documentation, right? A CEO from an 80-location urgent care group told me, obviously, that the payers are downcoding their claims, but they don't have the chart, right? So it's just judging the level of care off the diagnosis codes alone without ever seeing a word of actual documentation. But, obviously, the economics—this is really why payers get away with it. Is it really worth it for these groups to fight a $30 or $40 or $15 downcode? It's probably not. But when the payer does that to you 100 times, that's exactly why fewer than 1% of denied claims ever get appealed, and the payers know that, right? And I think what's even scarier is that it's not the downcode itself, it's that operators don't even know that the downcode happened. It's hard for them to notice it, right? The payer quietly knocks down a four to a three, and unless someone's watching every single claim, it just sails right through. You can't appeal what you don't catch, right? And so I think this is one of the scariest things facing urgent care operators today.
4. Regulatory oversight and high-tech fraud detection
Adam: It's definitely going to remain a big concern, but, of course, payers aren't the only ones using AI. And that gets us to our next force here, which is regulatory scrutiny. So regulators are also using AI to scrutinize public claims data. The public data they're getting from CMS, Medicare, and Medicaid, and scrutinizing that data is enabling them to target enforcement efforts in ways they just could never do before. It used to be the case that it had to be a whistleblower who was the trigger to initiate an investigation. Now it's an algorithm that's used by a federal or, in some cases, a state regulator. And you'll see a stat here on the screen about how use cases for AI at CMS alone have nearly doubled according to public records. This is part of a broader initiative, a collaboration really between HHS and DOJ that's called the Healthcare Fraud Data Fusion Center, and they list AI and cloud computing investments as a core part of their strategy. And this initiative is getting to be successful, right? They've had huge recoupments of payments by CMS, and you see seizures by DOJ. Some examples are here on the screen. But the most salient thing, I think, for urgent care operators to know is that enforcement is no longer targeted just at larger provider groups. And the last fact here of the four really backs that up. In April of this year, DOJ seized over $2,000,000 from a single-site wound care clinic. So the message they're sending is clear: with data analytics, no clinic is too small to escape notice. Guy, I want to throw this one to you. What are you hearing from operators about how high-tech, AI-enabled scrutiny is affecting day-to-day operations in urgent care?
Guy: Yeah. Absolutely. It's funny, I actually have a customer who faced this really recently. They're a fairly small practice, under five locations, super successful, great location. They were doing their homework the way most teams are still doing it, right? They set up rules engines in their EHR to hold any chart with high-risk codes for a coder to review. I'd say they were reviewing somewhere between 25% of their notes that way and also doing a larger share for newer providers. And that's pretty common practice. It used to be enough. There's still audit risk getting through when you're just doing spot checks here and there like that, but for most practices with lower resources, that's normal. For this particular practice, that wasn't enough. A pattern in their billing led to an investigation and eventually a settlement. It really just came down to someone making the same mistake and getting unlucky too many times. But as most of you know, fighting an investigation is time-consuming. It's expensive. It drains resources. And when there isn't any intentional fraud, a lot of people will tell you to unfortunately just go ahead and settle. This wasn't some kind of whistleblower making a complaint about a bad actor. It was a pattern of mistakes that just got caught by an outside data analytics team. That's why a lot of outpatient providers, rightfully so, are turning to AI to defend themselves.
5. Midcycle AI adoption across the urgent care revenue cycle
Adam: That's right, Guy. What you're seeing is that the vast majority of health systems have already adopted AI across the revenue cycle about 80%. Of course, health systems had the budgets and the volume to justify early adoption. Outpatient practices still lag behind them, but not for long. The cost of AI technologies have come down, and as we saw, the scrutiny is going up, which is encouraging smaller providers to get in and get started before they get hit. Outpatient teams increasingly see that technology is the only way to cope with these forces at the same time. After all, tech efficiency was the justification behind that CMS efficiency reduction on more than 7,700 codes. The question people have here is where do you start in the revenue cycle? Of course, one of the areas where we've seen really high tech adoption is at the front end of the revenue cycle. The front end is definitely critical for improving margins. A survey of our Centimeters leaders conducted by MGMA earlier this year estimated that 23 of revenue leak happens right there at the front end. These are often hard denials that can't be appealed, so it's really important to prevent them. So what does the front end technology look like? Well, it's smart scheduling tools to help optimize volume. It's voice AI that can handle eligibility verification over the phone. There's also smart tools for improving patient intake data so that a minor slip up like a typo doesn't generate a denial. The rate of adoption here at the front end is evident just from the market size for some of these tools. AI for patient scheduling alone is expected to grow to a $2,000,000,000 market globally by 2034 with much of that value, of course, concentrated here in North America. Now let's look at the back end. When you move to the back end of the revenue cycle, you'll see that this is where our Centimeters leaders think there's the greatest urgency. That's because this is where that surge in denials that we talked about before is hitting home and hitting bottom line. In a McKinsey study published in April of this year, fifty seven percent of rev cycle leaders said reducing denials was a top five priority for them. So what does implementation look like here? Well, right now, it's a lot of bots and tools for getting a handle on these elevated denials through automating the appeals process with things like AI agents. Now that sounds exciting. Right? But at an HFMA rev cycle conference in March, I kept hearing, even from the stage, this being referred to with a lot of resignation as a battle of the bots. And that's because RCM leaders are seeing this as a zero sum game. That's why they're turning their attention to the mid cycle. 72% of revenue cycle leaders said in an HFMA study that they expect back end denial management to shift to CDI efforts for denial management, and CDI sits squarely in the mid cycle. So let's go there. The mid cycle is now the new focus for AI adoption in health care rev cycle operations, and it's how we make sense of the two stats on the screen here. So only 13% of revenue leak according to the same MGMA study from earlier this year is attributable to coding mistakes. But 56% of RCM leaders say coding and documentation accuracy is a top five priority for tech adoption. These leaders understand that if you can ensure coding and documentation compliance in the mid cycle at the prebilling stage, you not only eliminate that 13%, you also reduce the size of the target on the back end for that appeals process, that battle of the bots. In other words, the mid cycle is where you're gonna get the highest leverage from here forward when it comes to AI RCM applications. Jake, I wanna come back to you on this one. Can you show us how one of these mid cycle solutions for denial management works in practice?
Charta for urgent care: Demonstration
Jake: Thanks, Adam. Happy to dive into a way that urgent care groups could leverage AI in the midcycle. So what you're seeing here is an AI documentation review or AI chart review platform. Basically, what that means is post-visit, pre-bill, reviewing 100% of your documentation for all the things that you would look for across coding and billing, clinical quality, and compliance. Anything that you would train a relatively intelligent human being to look for, you could build out custom analysis and use AI to reason around, again, 100% of documentation before anything goes out the door. And so I can show you guys an example. Basically, the right side is everything that's been pulled in from the EHR. The left side are the custom checks that your group has set up. It's important to note that all this is written directly back into the EHR. This is just like an external platform. But we can use this check as an example. This is an E&M check. Basically, three elements of MDM complexity are considered moderate. Because of that, this is a 99204, not a 99203. And you can see what the EHR writeback would look like. And, again, this would be autocorrected on the claim because the documentation already supports that. And it doesn't just stop there, right? You can look for missing diagnostic tests, missing CPT codes, modifier 25, and also look at documentation quality as well as compliance checks. Maybe you have tough measures that are coming down from certain payers in your region. These are all things that you could leverage AI to do and check across 100% of your documentation. And I think it's one of the most unique use cases in terms of getting ahead of all these things and issues in this really competitive landscape that we've been talking about. I'll also say one of the coolest things about using technology to review 100% of documentation is all the unique data and insights you may get into your practice, right? So this is an eight-location urgent care. You can see the performance across all the different locations, all the different providers, and all the different checks that you're doing. And you can even dive into a per-provider basis on how providers are doing over time. Again, how they are doing across all the checks that you've set up, and then even send providers feedback on how they're doing in terms of their coding and billing, documentation, clinical quality, compliance, all that kind of stuff. This really is just one example of a way that urgent care groups could leverage AI in the midcycle to help optimize, as I mentioned, revenue, clinical quality, and compliance as well.
Conclusion
Adam: Thanks for that, Jake. So just to summarize some of what we covered today, technology is increasingly the only way to cope with the margin pressures facing urgent care teams. Operational AI just isn't going to be optional when payers and regulators are setting the pace. And front-end and back-end AI RCM technologies are both worth looking at. They're well developed, and they're yielding gains for people adopting them. But with the back end settling into a stalemate, the focus is moving to the midcycle, which is going to be the highest leverage application going forward. Now I know we got some great questions submitted in the chat. Unfortunately, we're out of time, but we'll take the time to respond to each of you individually. At the top of the page, you'll also see a tab marked resources. You can click there to find a whole lot of other resources about how AI is impacting RCM teams, clinical quality teams, and care delivery teams in urgent care. So thanks for joining us, and thanks Jake and Guy for your insights.
