Latest / Off the Chart: A Business of Medicine Podcast / S1 Ep138: AI, layoffs and the law, with Christopher Mayer, J.D., of Frier Levitt
Transcript
- 0:00 Physicians face challenges every day, from difficult patient encounters to changing regulatory requirements at Copic, our commitment to you goes beyond providing reliable medical liability insurance. What sets us apart is our proactive approach, a 24/7 hotline answered by physicians, specialty specific guidance and CME accredited education and unwavering dedication to help you thrive, C, o, p, i, c.com, we're Copic here for the humans of healthcare here for you. 0:33 You can't just blindly accept what the AI tool has told you to do. You have to make sure that you know you protect yourself from liability. Welcome to off 0:52 the chart, a business and medicine podcast featuring lively and informative conversations with health care experts, opinion leaders and practicing physicians about the challenges facing doctors and medical practices. My name is Austin Luttrell. I'm the associate editor of medical economics, and I'd like to thank you for joining us today. In today's episode at medical economics, senior editor Richard Pearson sat down with Christopher Mayer, a specialist in employment law with the firm Friar law. They're talking about how artificial intelligence is reshaping workforce decisions, from algorithms quietly driving layoffs at major companies to the compliance risks the practices may face when AI tools have too much influence. Christopher Mayer, thank you for joining us, and now let's get into the episode. 1:37 Thank you for joining us today. 1:40 Thank you, Richard, and happy to talk about AI and its usage in in layoffs, which is the topic today. It's obviously a very timely topic. We're seeing more and more everyone how AI is impacting both the workforce and industry in general. So I think it's an important topic, and for your your audience, I think they will appreciate what we have to discuss today, 2:02 absolutely, and it's a great introduction, because we'll start sort of big picture, and then we'll drill down into healthcare a little bit, because there already have been some employment actions involving decisions around AI Artificial Intelligence that have taken place. Can you describe the current workplace or workforce situation around adoption of artificial intelligence and businesses laying off employees, you know, especially how they're maybe using artificial intelligence to guide human resources decisions. 2:32 Absolutely. Yeah, that's we're seeing it on on. We're starting to all see it on on two fronts, really. And the first front is that AI, generated, generative AI, primarily, is now being used by players to make employment related decisions. So they they will feed their, you know, their workforce factors into AI and try to determine, using AI and the algorithms in AI, you know, determine who should be eliminated, what jobs are redundant can be replaced. So we're seeing that, you know, obviously, more and more and a lot of that's going on behind the scenes, but there it does leak out from companies you know, that have used AI for these purposes. And Verizon is kind of a recent example we can talk about that. You know, Verizon did about 13,000 layoffs recently, and they didn't really cite AI as part of it, but it kind of leaked out that AI was in some ways, behind the scenes in some way. And the other thing that we're seeing, you know, in addition to the use of AI to make employment related decisions, layoff decisions, is that AI is obviously disrupting workforces across all industries, and we'll talk about healthcare. But it doesn't matter what the industry is really every industry is going to be impacted, it appears by AI in some way, and that is resulting in some redundancies, elimination of jobs are being considered, and there's a lot of fear out there. Obviously, none of us understand fully what AI means for the future, and I think that includes the people who are developing these AI tools, and are investing so much in it, we don't fully know where it's going. And no one knows fully you know whether or not their jobs are going to be impacted by it. And I think you know in the tech industry in particular, I think you know when AI first started coming out, and the rumors about it, I think coders and other people in the tech industry just assumed that they were going to be a big part of it, and their jobs were safe forever. And that's not how it's played out. I mean, AI, as it turns out, is making a lot of those coding type jobs completely irrelevant, or, you know, unnecessary, because AI can do it faster better. You know, there needs to be some human element still, in terms of programming it or plugging in the information. But, you know, a lot of those jobs are going by the wayside. So it's, it's hard to really predict, you know, the impact completely. But the good thing for healthcare is, healthcare is one of the industries that is, you know, primarily the remote, for the most part, immune from a huge impact of AI replacing jobs. I mean, obviously healthcare. Or is a patient facing industry and human humans will always be a big part of that, and that's that's not going to change. 5:07 And it's a great segue, just to drill down a little bit, maybe a little bit more on healthcare, at least as of right now, February 2026 Have there been any major AI related layoffs across the healthcare sector? That's a 5:20 great question there. There haven't been many public ones. I mean, you know what we're seeing more like the Amazons of the world, where the Amazon recently, starting in October last year, eliminated 30,000 jobs. And those were good, high paying jobs, you know, kind of across the board. And they, you know, they specifically said that this was aI driven. It says we're, you know, we're integrating and adopting AI tools in our business. We're going that route. There haven't been a lot of prominent examples in healthcare, and part of that is because I think that, you know, the layoffs will be smaller, you know. And if you're talking about a small provider, which I know is a lot of the audience here, they're never going to be covered by, say, the federal or state WARN Act, so they're not going to have to report a layoff to a provider or to the state or to the, you know, the folks that have to be notified under the WARN Act, because their layoffs just aren't going to be covered by it. And a lot of those providers just aren't covered by the warrant act to begin with, what we're going to see more of, I think, is with larger health systems when they're making reductions, and that's kind of the most prominent one that we've seen so far out in Utah, a health system revere health, I believe, is the name of it. They eliminated almost 200 jobs, nearly 7% of 7% of its entire workforce. And that was a largely AI driven layoff. It was a lot of coders and other folks that you know are expected to start to lose their jobs in the AI world. 6:50 Well, no, it's an interesting point that I think you touched on just a few moments ago, and it's sort of that, that dichotomy that takes place in healthcare, where you have hands on work, where you're actually working with patients. But then there's also, frankly, a lot of head work that involves, you know, physicians and other clinicians getting the education, the training experience to recognize conditions. And I'm just kind of wondering, I mean, we're already seeing how AI is being used as a tool to supplement that head work, so to speak. 7:19 Yeah. And I think for small providers, you're not necessarily going to see a lot of public results or layoffs and things like that. What is going to happen is it's going to be more behind the scenes. And I think small providers may benefit more from the transition into the AI world, as much as anyone in we're seeing that with, say, anthropic and other generative AI companies, when they go in, they target an industry, whether, you know, and more recently, I think it was chat GPT did this in the investment banking world. They, they created a training run, as they call it, to basically replace Junior investment bankers. And so, you know, as these, these companies focus on, you know, what, what they can do and what they can replace. They're, they're making a lot of existing software tools, or eventually, they're expected to, and that's why we're seeing a huge impact on the software industry in general, obsolete, you know, they'll, they'll be able to provide similar, maybe even superior, software tools at a at a much reduced cost. And I think a small provider could certainly benefit from that. But what I'm seeing is that small providers are also early adopters of AI usage, just in, you know, in their general life. And I think that's in part because, if you're a physician running a small practice, you know, you're it's just like anyone who runs a small business, you gotta, you got it. You got to do everything. You know, you may have, you may have accounting people, you may have finance people, but you you're hands on, and you've got to be in that. And so I'm, I'm seeing those folks doing a lot of, a lot of the outside work, a lot of the administrative work, using AI, and it doesn't mean they're accepting it as, you know, the as a panacea, or, you know, the that the answers that they're getting from Ai they're accepting is accurate always, I think they're just starting to adopt it and use it to make research things and make, you know, some decisions. 9:14 A great segue to start talking about that intersection and that moment of making decisions regarding human resources. Can you talk about and maybe this is still very new, but what is exactly the intersection between human resources and employment law and AI, there are, I know, different points that are going to sort of exist under that umbrella of human resources and employment law. But what are, I guess, maybe, what are some trends that you're seeing, or what would you predict? Well, I 9:44 mean, certainly any sort of service facing industry or business, you know, they have to carefully address and regulate how their employees use AI, so that a lot of that's going on in terms of adopting policies. But I do think. Think, you know, in healthcare in particular, there's going to be an impact on, as we talked about, folks who do coding, you know, claims like, there's, there's going to be a huge impact on that. And that's where I think AI is really going to come into play over time and start to to affect it. But from, from the HR perspective, you know that what what HR people have to be mindful of when they're doing a large scale reduction in force, and for a small provider, a large scale reduction is, you know, three or four employees. It doesn't have to be 5060, employees, but the main thing they're going to have to be mindful of, just like you have to be mindful of in any reduction. This is no different than any other reduction that you're doing is the is the impact that it's going to have across protected categories. So what that means is you have, you still have to make sure before you go through the layoff, and if you're using an AI tool to tell you who should be eliminated, you're going to have to sit down carefully. And sometimes this should be done through counsel. So you can, you know, have the attorney client privilege attached to it, but that's kind of another matter. But look at the impact that it's going to have, and if it's going to the layoffs that, AI say, has suggested that you do, if it's going to eliminate, you know, five or six people over the age of 40 and no one under the age of 40, that's not a good look, and that's a problem. And you know that not only is that a problem in terms of potential liability, but if you're going to do a reduction where you're trying to get a release in exchange for severance, which is a very good business practice, and something that you know any sophisticated employer does, you're going to have to disclose the age ages of the people who are impacted by the layoffs, and the ages of the people are not impacted by layoffs under federal law to get that release. So the Age Discrimination Employment Act, which is the federal law I'm talking about, sets forth very particular requirements for a reduction in force that impacts, really, more than one employee, a group of employees. And that is one of the things that you have to do. You have to show who by age. You know. You don't have to identify them by name, but by job title and by age is being impacted. And so if you're seeing as an employer a disparate impact, you know you're the employees who are being impacted by that are going to see it too. And not only that, you have to tell them they should go and consult with a lawyer before signing the agreement. So they're going to take that lawyer is going to look at that and go, don't sign it. You know, we might be able to sue over this if they're going to go forward with it. So that's a long way of saying, you know, you just have to be very mindful of the impact, and that it's not limited to age. I mean, obviously any category that's protected by law, race, gender, all the you know, the protected categories, you have to make sure you're looking at it and determining whether or not it's, you know, going to have a disparate impact on your workforce, and if it is and statistically, it doesn't look good. And there are tools that you can plug that data into that will tell you whether it's going to have an improper statistical impact. You know, you might have to make adjustments to the layoff now, the this analysis is more appropriate, as you can imagine, for a large scale layoff, whereas, you know, in a large scale layoff, if there's a statistical anomaly, that's a problem. You know that. So any sort of statistical or, excuse me, any sort of statistical anomaly would be sorted out in a large scale layoff, you know, like, if you're doing five people and three happen to be over the age of 40, well then there may not be much you can do. You know, that's that's a little different. But if you're doing a large scale layoff and there's a huge impact on one protected category. That's a problem. I mean, it really is so. But even in a spotlight, if you just have to be mindful of the impact it's going to have, who's going to be affected by it, you can't just blindly accept what the AI tool has told you to do. You have to make sure that you know you protect yourself from liability, 14:01 you know what? And this was a point. I don't mean to belabor the point about age, but I guess I just wanted to ask if you might lend even a little bit more clarity toward the notion of if an employer is not allowed to ask a person's age when they apply for a job to avoid discrimination, how are they able to avoid potential liability when you're making a layoff if you're not totally sure of a 14:26 person's age, that's a good question. And so employers do have access to the information. They have access to the birth dates of their employees, and most employers have to do annual EEO reporting, so it requires them to gather some of that information. Although a lot of the information, you know, folks don't have to provide it. It's optional, like race and you know, things like that. So you don't always have all the information. Age is one that employers do tend to have all of it. So, you know, you do know the ages of your workforce just because on certain pre employment and early. Employment documentation, you have to disclose your age, but other other categories, you don't necessarily know it. So that's in that instance, it can be a problem. So what you have to do when you're doing a layoff, and if it's a large number of employees, you put together what's called like an employee census. So you're going to prepare a chart of everybody that's included in the layoff, by name, by job title, by compensation. You know, you do all those things, and those things are sometimes behind the scenes as factors, but then whatever statistical information you have about them, whether it's race, national origin, you know, you fill out those. You know, those categories, if somebody's out on a disability, leave, you know, you check that box and you put it all in there, and that's important, so that you can see it all together. But if you don't know it, you leave it blank. You can sometimes try to guess, but that's, you know, not always a good, good system, as you can imagine. But it is important to gather that information together, and then you want to see the people who are not being impacted by it. So, you know, if you're looking at a job criteria and you're trying to eliminate it, half of the people in that job category, and you've picked half, you know whether they're poor performers or what have you got to see who is staying by the same criteria you need to compare and see and that, you know that you can present to an attorney or, you know, a consultant who will crunch the numbers on that too, if it's if it's too many people involved, you know, if it's a smaller scale, I think an employer can do that themselves. 16:30 And this is something that wanted to ask about, sort of two different elements, because sometimes, in fact, medical economics, frankly, we cover a lot of policy at the federal level, and there are certain federal rules, especially regarding, you know, discrimination that govern employment law. Can you talk about any kind of federal bills, initiatives, policies that are in place right now that affect how AI is used in employment law and human resources? 16:59 Not not at the federal level, really. So most of what we're seeing is going on at the state level, the, you know, the current administration. So for example, the EOC, what one of their initiatives that they were tasked with looking at was reverse discrimination. So they, they've, they're kind of focused on things that they traditionally have not been that focused on. And at least from what I'm seeing, the administration is more of a proponent of AI, and so they're not seeking necessarily to regulate it yet. And that's, you know, that's obviously an issue with AI in general. It's largely unregulated. So there's, you know, there, there will eventually probably be more regulation, but right now, there's not a lot. But where we are seeing attempts to regulate AI in terms of its impact in the employment world, is at the state level, and California, as usual, is one of the states that you know, kind of has jumped out. They adopted some, some regulations that just, you know, kind of regulate how AI is used in hiring, firing decisions. Just that they want to know if employers are using it, and you know how it will. It basically says you can't discriminate in that process, which is obvious. And you know, in terms of the other laws still apply to an employer equally, but they're just focusing in on AI to try to, you know, make, make employers more mindful of it, but now, not at the federal level, not not much that I'm aware of now, 18:25 and I think you've touched on this in some of your answers, just by implication. But this one, I'll ask to ask you to sort of look into the crystal ball, so to speak. And can you make any predictions about potential litigation or enforcement trends that might involve artificial intelligence in employment law and human resources. 18:44 I do think there will be challenges. And again, I'm primarily coming at this from the employment world, but I do think there will be challenges to employers who are using AI to make employment decisions. And again, that isn't always widely known. I mean, these decisions when they're made are done in secret, and often are done with counsel. So but it does tend to leak out. So I think employees often find out if an employer is using a tool because there is some level of management involved in it, and they may share that with other folks. And so what you will happen? What will happen if there are these types of challenges to it, it'll be very important. If they're, you know, they're not putting a lot of information into a public AI tool. I mean that that will be very important, like you can't be putting private information into a public AI tool, information that's protected, as you know, private health information, obviously, in the in the medical industry and medical world, that's extremely important. But if there are challenges to that, it'll, it'll, it'll be interesting, because they'll be largely based on speculation. In other words, you won't be able to find out until you sue and you know you're saying that there's some sort of bias built into what. Of our tool that they're using. And that's probably, to me, that's the main concern. I mean, we have seen that some AI tools have inherent biases built into them because of, you know, how they're programmed. And we saw that with must tool, with grok, and we've seen that with some of the others. And those, you know, they can go in different directions. And I, you know, without getting political about it. You know, they obviously, they can have bias, and it really depends on the information that's fed into the AI tool or that it has access to. So that, you know, that is one concern, but the bigger concern is what we already touched upon, like, and this could be individual claims. It could be, you know, class action, multi plaintiff employment actions where there's a disparate impact, so, you know, some sort of challenge to, you know, a large, typically large could be from the EOC, but more more likely from, you know, a private lawsuit to an AI related layoff that seems to have had a disparate impact on a certain category of folks. And, you know, that's inevitable. I think that's going to happen it. You know, obviously we touched upon ways to avoid being the target of that type of lawsuit. Just be careful, be mindful of it. But it will happen. It always does. And you know, there are challenges already regularly to layoffs for having a disparate impact, and I think it'll be very interesting when those first cases come along, because we talked about the fear and the misinformation. So putting a case like that before a jury, I don't know how I have an idea of how a jury generally might act. I don't, I don't think they're going to be happy with it, you know, I think jurors will, will not like it, and so that that's that would be a huge problem, and they're just going to assume that that the employer really had a pretext and wanted to discriminate and is trying to hide by day, I to justify it. I think that's how jurors will and jurors are, you know, very straightforward and honest about these things. And they, they like to punish employers who run want to run astray in a sense. 22:14 Hey there. Keith Reynolds here and welcome to the p2 management minute in just 60 seconds, we deliver proven, real world tactics you can plug into your practice today, whether that means speeding up check in, lifting staff morale or nudging patient satisfaction north, no theory, no fluff, just the kind of guidance that fits between appointments and moves the needle before lunch. But the best ideas don't all come from our newsroom. They come from you got a clever workflow, hack, an employee engagement win or a lesson learned the hard way. I want to feature it. Shoot me an email at K Reynolds, at MGH, lifesciences.com with your topic, quick outline or even a smartphone clip. We'll handle the rest and get your insights in front of your peers nationwide. Let's make every minute count together. Thanks for watching, and I'll see you in the next p2 management minute. 23:04 You know what? If I may switch gears slightly, one of the items that I know you've written about in the past has been non compete agreements, used especially in health care and medicine. Earlier this year, the federal trade commission made clear its attitude toward enforcing non compete agreements. How would you describe the current atmosphere around federal enforcement, and particularly non competes for physicians and other clinicians? 23:29 Well, yeah, we saw the FTC a few years back try to aggressively regulate non competes. And there was, there were a lot of questions on whether the FTC even had any jurisdiction over that. I personally believe they did not have jurisdiction over that, but they were trying to assert their jurisdiction broadly, and that was shot down in Texas. And you know that rule that they had, that the FTC had adopted, was shot down by a Texas court and joined, so it's no longer in effect. So you know where we are right now that the federal at the federal level, non competes really aren't regulated like when I when I deal with or look at non competes, I'm primarily concerned with state law, because that's what matters so and in every state, it's completely different. I mean, so you have to where employers who have multi state functions or practices run into trouble is when they have one non compete agreement for, you know, all employees, and they try to use it in every state, and that just doesn't work. I mean, non competes are only appropriate first of all, for certain certain types of employees. I mean, a low level employee should never be bound. In general, should not be bound by a non compete unless they have access to some sort of special information, you know, and which suggests that they may not be that low level, right, if they're doing something like that. And you know, you have to, you have to have non compete. So you have to be mindful that there are different laws depending on the position that you're talking about, too. So if. Physicians. You know, if we're going to focus on physicians, there is seemingly a trend nationally to move away from non competes with physicians, but in most states, they're still enforceable. So you you know, and when you're running a medical practice and you start to get larger, a non compete is a very effective tool to have to protect your investment. You're hiring physicians, whether you're hiring a young physician or, you know, an experienced physician, where you put your paying this physician a lot of money to bring them over. You know, it's an investment, and so they do protect your investment. No one wants to spend a lot of money in training, and, you know, providing other tools to physicians just to see them, you know, take that investment and jump to another employer a couple years later. So they are effective to, you know, protect those investments. But again, you have to be mindful of, of, you know, the what state you're operating in. And you know, there are a few different levels. Like California is obviously the classic example, they ban non competes there, you know, there is no non compete that is enforceable in the state of California. So that you start with that proposition, that's a statute. There are other states where, you know, they're regulating certain industries. Pennsylvania is an example. They Pennsylvania last year adopted a statute that really limits the what you can do with a physician in a non compete. So it, first of all, it has to be limited, and this is only for non competes going forward. This didn't apply to hold nine hold agreements, but in Pennsylvania, a physician cannot be bound by a non compete. That's longer than one year. And if an employer fires a physician, it's unenforceable. You can't enforce it. It's only if the physician leaves on his or her own accord. You know, in other words, if they resign, maybe you can enforce it, but otherwise you can't. And then there are other states where there aren't statutory schemes like, say, New Jersey or New York, but non competes are generally enforceable against physicians under certain limitations, you know, they need to be very narrow, whether it's a year or two, you know, no longer in New Jersey. For example, a large geographic restriction is not generally enforceable, especially in urban areas. It needs to be tight. It needs to be, you know, say, 15 or 20 miles and no more than that. So that's with non competes. It's very important to be if you want to have one that's potentially enforceable. And they're never guaranteed to be enforceable to begin with, because they always depend on the circumstances. And there's a human element, which is the judge who's enforcing it. So even if there's not a statute prohibiting it, a judge might be favorable to enforcing non competes or not. I mean, you so there's, there's a lot that goes into play. But if you want any chance that it's potentially enforceable and to act as a deterrent, which is where I think they're mostly they're the most valuable, you need to make sure it's compliant with whatever law the state where you're operating that, or where the physician is based that that's the critical consideration. So, you know, just having a one non compete that you think you can use forever, it doesn't work. 28:08 It really doesn't. And you know, just to continue on that train of thought in, in, from an employer's perspective, I in, I know there's a lot, there's a lot of debate under the healthcare umbrella, so to speak, about the benefits and drawbacks of non competes regarding especially physicians who may be young in their careers, or physicians who are considering changing employment, if they sit down at that negotiating table and the hospital or healthcare system or another group of managing physicians presents to them a non compete agreement. What should they do? 28:40 Well, this is going to sound very self serving, but I think they need to consult with an attorney. And you know, for a variety of reasons. I mean, we just touched upon it, the law in different states is completely different, and a local practitioner in particular will know the ins and outs of how you know they're enforceable in that state. May have appeared in courts recently, where this, you know that relevant courts where they can tell you where, you know where the judges are on enforcing non competes against physicians. So you just, you need to get legal advice, for short, before you sign it. I would say, you know, don't, don't jump into it. Don't be pressured to sign a non compete before you talk to an attorney, and you know, you may learn that, well, maybe it's not enforceable. So sometimes you can tell the employer, well, why are you asking me to do this? It's illegal in the state or or, you know, even though they're asking you to sign it, you know, it's illegal in the state, and you don't necessarily need to be worried about it going forward. So they're, you know, those considerations come into play. But also, if you have a non compete in place already, and you signed it 15 years ago, in particular, the law may have changed. So if you're going to leave an employer to go somewhere else, get legal advice again, the law may have changed, or an attorney can negotiate with your new employer, the new employee. Employer can take a look at your existing non compete and make a decision on how to bring you over. That doesn't violate the non compete, you know. So you can work outside of the restricted area if the employer is large enough, and your attorney may be able to get some protection for you in the contract in terms of being indemnified and protected if you are sued individually by your former employer, so you, you know, you think you're doing nothing wrong, but that doesn't mean your former employer isn't going to make assumptions that you are violating the non compete and come after you. And if, if that's the case, you want to make sure that you're protected by your new employer who wanted you to come over knew about the non compete. You want them to, you know, not leave you high and dry in the event of litigation and to protect you. 30:46 That point about, particularly a physician notifying a new employer, that's an interesting nuance, and I don't think one. I frankly, I don't think we've really covered that angle at all. So I'm glad you brought up that point, because that was a new one to me. And the possibility, the prospect of getting a new employer to sort of lend that aid that sounds like that could be a helpful tool 31:06 for physicians. It is. And the worst thing you can do when you're leaving and you're bound by a non compete is to lie to your former employer about, deceive your former employer about what you're planning to do. Oh no, no, I'm not going to work and then go somewhere else. That's when you get into trouble. And the same thing with your new employer. Don't, don't put, you know, if they ask you the question, obviously you have to disclose that you have a non compete, but don't hide it, you know, let your new employer know. I got this restriction. I'm worried about it. What do you want me to do? And let you know first, let their legal team opine on it. Look at it. You know, offer their opinion. I still think it's important to potentially have, depending on the circumstances. Have your own separate counsel in that situation, as we talked about. But, you know, let their legal team look at it. Don't hide it from your new employer, though you don't want 31:51 to do that. One question I always do like to ask, though our main audience is primary care physicians, yes, what would you what would you like to say to them? Or what would you like them to know? 32:01 Oh, well, that. That's a good question. I mean, I hadn't thought about that. But, you know, in terms of AI, I would, I would say to them, you know, don't be, don't be fearful of AI. It's, you know, we, there's a lot of misinformation. There's a lot of assumptions that it's going to be more harmful than do good. And we, you know, we don't totally know, but I think for physicians in particular, it's, it's going to, it's going to supplement the care that they can provide some of these AI tools. And I think a lot of physicians already finding that to be the case, and I think hopefully, you know, over time, will be viewed as more of a positive. Now, I'm not, you know, I'm not saying that from someone who is on the inside of AI in any way. I just, I tend to be optimistic, and I hope it will be a useful tool for folks over time, and it won't necessarily result in the widespread decimation of jobs that we all seem to fear right now. 32:49 I'm Richard payer chin, reporting for medical economics. My guest today has been attorney Christopher S Mayer, a specialist in employment law with the firm fryer Leavitt. It's been a great conversation, and we've covered a lot of ground. Thank you so much for 33:03 joining us today. Thank you, Richard. It was, it was a great conversation, as you said, and I look forward to speaking with you more in the future. Once again, 33:21 that was Christopher Mayer, a specialist in employment law with the firm Friar Leavitt, speaking with medical economics senior editor Richard periton, on behalf of the whole medical economics and physicians practice teams. I'd like to thank you for listening to the show and ask that you please subscribe so you don't miss next episode. As always, be sure to check back on Monday and Thursday mornings for the latest conversations with experts, sharing strategies, stories and solutions for your practice. You can find us by searching off the chart wherever you get your podcasts, and if you'd like the best stories that medical economics and physicians practice published deliver straight to your email six days of the week, subscribe to our newsletters at medical economics.com and physicians practice.com off the chart, a business of medicine podcast is executive produced by Chris mazzolini and Keith Reynolds and produced by Austin Luttrell. Medical economics and physicians practice are both members of the MGH Life Sciences family. Thank you.