The Group Dentistry Now Show: The Voice of the DSO Industry – Episode 232

Ranked the #1 DSO Podcast!

Welcome to The Group Dentistry Now Show: The Voice of the DSO Industry!

This panel discusses dental operations and leveraging AI to assist with RCM. Nicole Collard, Technology Operations Mgr. at Tend, Dr. Greg Wu, Owner of Emerson Dental, Troy Andrews, Product Mgr. at DentalxChange & Dan Feimster, VP of Product Mgt. at DentalxChange share their thoughts on:

• AI as a game changer for efficiency
• The importance of data interpretation
• Embracing change with confidence

To learn more, you can visit https://www.dentalxchange.com/

You can connect with Dan Feimster on Linkedin – https://www.linkedin.com/in/dfeimster/ or Troy Andrews on Linkedin – https://www.linkedin.com/in/troy-andrews-a55ba2bb/

To learn more about Tend visit – https://www.hellotend.com/

You can connect with Nicole Collard on Linkedin – https://www.linkedin.com/in/nicolecollard1993/

Connect with Dr. Greg Wu, Owner at Emerson Dental here – https://www.linkedin.com/in/gregory-wu-7708211/

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DSO Podcast – From Challenges to Solutions: How AI is Transforming Dental Operations & RCM

Welcome to the Group Dentistry Now Show, the voice of the DSO industry. Join us as we talk with industry leaders about their challenges, successes, and the future of group dentistry. With over 200 episodes and listeners in over 100 countries, we’re proud to be ranked the number one DSO podcast. For the latest DSO news, analysis and events, and to subscribe to our DSO Weekly e-newsletter, visit GroupDentistryNow.com. We hope you enjoyed today’s show.

Bill Neumann: Welcome everyone to the Group Dentistry Now show. I am Bill Neumann and as always we appreciate you watching us whether it’s watching us on YouTube or on groupdentistrynow.com or maybe you’re listening to us on Apple or Spotify. We certainly appreciate you checking in and your loyalty to the podcast and we always have great speakers and topics, and we’re going to focus on AI and revenue cycle management today. And everybody on the podcast is new, the first timers, which is awesome. We have with us Nicole Collard. She is the technology operations manager at Tend. We have Dr. Greg Wu. He is the owner at Emerson Dental. They’re based in Massachusetts, two locations, multi-specialty. We have Of course, Dental Exchange, who is actually sponsoring this podcast. Thank you, Dental Exchange. We appreciate that. We have Troy Andrews, who is the product manager at Dental Exchange, and Dan Feimster, who is the vice president of product management at Dental Exchange. So we’ve got a great panel discussion, talk all about AI solutions and RCM and how dental exchange is really helping out when it comes to that. Nicole, a little bit about your background. Can you get us on up to speed on what’s going on at Tend?

Nicole Collard: Yeah, I’ve been at 10 for four years, and we’ve really focused on integrating tech across everything that we do to try and make access to care easier for our patients. And we have 31, 32 locations actually now across a couple of different markets in New York, DC, Boston, and Atlanta. So we’re kind of spread out all across the country on the East Coast at this time.

Bill Neumann: Excellent. Yeah, we had Dr. Salerno on not too long ago. Always a great guest. We’re glad to have you and get your perspective on things that tend. Dr. Wu, a little bit about your background and also a little bit about Emerson Dental. I was reading your bio and you’ve got a lot going on, a real deep background and interesting story. So, I’d love you to share that if you wouldn’t mind.

Dr. Greg Wu: Absolutely. Thank you for having me. I’m a dentist first. I purchased a practice back in 2010. I’ve been practicing for 20 years. This year is 20 years. I’ve slowly grew my practice over the years. It was started as a solo GP office and I started to integrate the different specialties and grew it to a multi-specialty, two-location practice. I’ve always been fond of technology, so I’ve always been an early adopter of new techniques. And, you know, that’s here for me to tell that story. I’ve also suffered through some medical issues. Three years ago, I had a stroke and I removed myself from clinical care. So even more so, having technology where I can, you know, run efficiently was so important for me.

Bill Neumann: Thank you, Dr. Wu. Troy, why don’t we, a little bit about your background, Troy.

Troy Andrews: Yeah, my name is Troy Andrews. I’ve been with Dental Exchange for about a year, but 20 plus years in product management focused on revenue cycle. I love revenue cycle. I manage two of our rev cycle products, an eligibility product and a reconciliation product. Both of them have some AI components. So I’m excited to be participating in this today to talk about that.

Bill Neumann: Thank you, Troy. Dan, a little bit about your background and maybe you can talk a little bit about what it is Dental Exchange does.

Dan Feimster: Yeah, that sounds great. Again, thanks for everybody joining the calls today. Again, Dan Feimster, similar to Troy, I’ve been working in product management for about 20 years and started in the medical space and have transitioned over to the dental space primarily as my focus. As the head of product at Dental Exchange, I am privileged really to get to work with a great team of people like Troy and others that are building from our flagship clearinghouse business to all of our product innovations that Troy is responsible for around eligibility AI and reconciling AI. Those solutions and generally the entire portfolio is designed to help simplify the claims management process, automate transactions in the revenue cycle space that facilitate things like treatment planning, or even just the reconciliation of posting a payment. and ultimately trying to enhance as much transparency that we have between a dental practice and dental payer ecosystems. Outside of work, I get to be a great dad and use the things I learned in dentistry and the product management space to help, you know, are my kids aligned around their endeavors. And so thanks for having me today on this conversation.

Bill Neumann: Great. Thanks, everybody, for the intros and insights on your organization. AI is everywhere in the dental industry. I guess it’s everywhere, right? Not just the dental industry. We talk about this a lot on this podcast. There is definitely a technology and an AI overload. There’s so many different solutions coming at you as an owner, as a DSO, you know, technology person managing a lot of this. So much coming at you at once and it’s changing so rapidly, right? So even a solution you may have, it doesn’t look the same that it did 90 days ago. And it can be pretty overwhelming. So hopefully we can kind of, at least when it comes to what Dental Exchange does and some of the technology and AI solutions they are bringing to the table, we can paint a clear picture about how you can leverage those solutions and how Tend and Emerson Dental have leveraged those solutions. Start with you, Dan and Troy. Talk a little bit about eligibility AI. And when we talk about AI, what does that actually mean? Troy, do you want to kick things off?

Troy Andrews: Sure. You’re right. AI is everywhere. And a lot of times it is what you want it to be. I think of how AI interacts with our products in that an AI agent or an AI data model never gets bored and can see connections that humans can’t. So when we look at eligibility, we’re trying to figure out This is the beginning of the revenue cycle relationship between you and your patient. How do we make sure that we get the correct data? So you know exactly what to collect at the point of service. You know how the claim is gonna be dealt with when the payer gets it and gets ready to pay it. And what you can expect in the collections process and the revenue cycle process from that very beginning when that patient is scheduling their appointment, to the end, when you’re reconciling their claim and closing out their AI, closing out their AR, an AI agent in between those events can look at everything that happened and tell you, here are the things you need to think of when you’re designing your treatment plan. Here’s what you can expect to collect. Here’s what you did collect in the end. And how do those two things work together? So for me, I think of AI as how do you find the tiniest little connection between what is going on with the patient and the payer, and then how you are dealing with that, that relationship throughout the treatment of that patient. So it is exciting. It is everywhere, but what we are trying to do is, is use it in a way that is useful to the practice and to the patient and use it to enhance anything that we’re going to present as a product.

Bill Neumann: Thanks, Troy. Dan, is there anything you want to add to that?

Dan Feimster: Yeah, I would. The areas that we’re invested in, as Troy was describing how AI could be used, is if you separate it into two things, one is the administrative functions. So we use AI around what the industry might call robotic automation. And so this is an area where the workforce that practices, or our payer clients as well, have invested just the amount of people we can automate much of that function, and AI informs the functions of what we’re doing. And then if you go to the other side of that spectrum, AI is also a learning intelligence. And so the complexities that it takes to understand some of the things that happen in motorcycle management What did that code on that ERA mean and how should I interpret the next best action? So, we’re looking at it from a spectra of how we would deploy it from automation to intelligence. And so, I just want to say that’s how our portfolio is evolving and how we’re enabling AI in the system. Thanks, Dan.

Bill Neumann: Nicole, what drew you and Ten to explore an AI-driven solution like Eligibility AI?

Nicole Collard: Yeah, so previously, we’ve gotten basic eligibility. We really standardized that into our process. But unfortunately, the data is kind of stale at times, just because it’s just a data file. So we were trying to figure out a way to get more accurate information up front, specifically when we verify our members, and quicker as well, just because access to care is so important for us. as an organization. So we have a lot of same day availability for when it comes to emergency visits, things like that. So we need to be able to get that information as quickly as possible without having two, three people in every location working on verification. So that’s what really drew us in is we really wanted to see how we can make it faster and how we can make it more accurate up front for our patients.

Bill Neumann: Great. Dr. Wu, similar reason or was there something different?

Dr. Greg Wu: So similar reason, and I’m sure I speak to a lot of the private practitioners out there. Hiring and retaining employees is very difficult post-COVID. We’re challenged with staffing issues. So things that we can adopt to automate and take the tasks so that we can have our team members do patient-facing tasks and let AI take on the things that we can do in the background and then we can make it more efficient and utilize everybody in their correct roles. The biggest frustration, I think, when you’re trying to do eligibility is being on hold or if you’re trying to log in for everything. So if you can save time, I mean, that’s the only thing we can’t make more of is time.

Bill Neumann: When you decided to bring in eligibility AI, can you talk a little bit about the integration process, Dr. Wu?

Dr. Greg Wu: Right. So one of the things, obviously, when you go on these payer sites is the second factor authentication. And so, you know, we work with Curved Dental Software and they’ve always been an innovative software. They’re always continually approved. As soon as I saw that there was this option for us to trial eligibility plus, I was like, sign me up. Anything that will make our operations smoother and better, I’m all for it. Now, obviously, as an early adopter, I don’t have as many people to ask, hey, how do you handle these things? So that’s the first thing I’ll say. But, you know, I’m excited and it’s been a game changer. And obviously, it’s already saving time as from the partners that Dental Exchange has implemented. In eligibility plus.

Bill Neumann: And similar on the integration side with you attend.

Nicole Collard: Yeah, I mean, like I said, we use, we get a lot of like just raw data files for basic eligibility. So it’s actually kind of a layered process. So we get data from as many places as we can to make sure we have a full snapshot. But it was pretty seamless for us, to be honest, when we integrated the AI dental exchange responses. And we were an early adopter as well, specifically for this platform. So it was a lot of verifying the information, making sure it’s accurate, and it was looking great from patient portal. So we love that.

Bill Neumann: So you’re both early adopters, which is great. You don’t see a lot of those, right? If we kind of look at the bell curve, right? There are very few. How about hesitations from the team or some challenges maybe during the adoption as you’re kind of making this big change? Nicole, anything that stands out?

Nicole Collard: I think the biggest hurdle that we had to go over was The way that portals interpret your information is pretty different. So we had the challenge of kind of streamlining that. And I mean, that’s where AI came in is MetLife and Delta Dental don’t refer to things the same way. So it’s how you interpret that data. That was probably our biggest hurdle up front, but with AI, it’s actually really streamlined that because it’s been able to interpret what does this mean for this payer? And what does this mean for this payer?

Bill Neumann: Great. Dr. Wu, did you have any challenges or any hesitation from the staff?

Dr. Greg Wu: So I wouldn’t say challenges, but let’s be honest, nobody likes change. So if you say you’re gonna change something, the first thing that people will say is, wait, what is this? So it wasn’t necessarily a challenge, but introducing anything new, you always have a little hesitation, but as soon as they saw what this could do, it became a game changer. They could see that it was gonna save them time, and the team saw how it could be beneficial to the practice as a whole. You know, in the end, I mean, anything we want to do new, it will always have some sort of challenge.

Bill Neumann: Absolutely. So focus on workflow and efficiency. This question is really directed more towards Dan and Troy. So you have eligibility AI, and how does that differ, would you say, compared to real-time eligibility? Dan, I don’t know if you want to. Take that one.

Dan Feimster: I am happy to do so. A couple of differences to highlight. In a basic transaction in general, which has been around for 30 or 40 years in terms of ANSI-based transactions, Nicole highlighted this already, the payers are not providing a normalized response. So when you’re looking for information, it could be in different areas of the response. And so part of what AI does, it takes the structure of the information and actually puts it in the same place every time based on what the user is going to see in context of their screen. So that’s one area of highlighting it. The other really big investment that we made around the information that’s actually contained in those sections, if there is a component and a data element that we’re talking about the plan type, It would talk about some frequency or some other type of limitation. It actually can pull that information out in a context and put it into a usable piece of information that goes into your treatment planning or otherwise. And so AI has seen a big investment at how you could actually use the information versus having a human have to go through and interpret or find it. And so those are two big areas that we had to address. Great. Troy, anything you’d like to add?

Troy Andrews: Yeah, I think one of the things I love about product management is that your product develops as your clients need it to develop. And I had a manager at a previous company that said, you know, the people who designed the iPhone didn’t set out to put calculator companies out of business, but in a way they did. So that we should always be looking for what is the calculator inside your product. And we’re working on a project right now with both Tend and Curve. to sort of evolve eligibility AI from being appointment focused to, we also need to know the results for these 20 very specific codes that have nothing to do with how the product was designed. So we’re putting that into the product, we’re evolving the product into something that is a whole new way to think about how it gets information. That started with requests from Tend, curve that are turning into a really great new feature in the product that I don’t think I would have thought of if I hadn’t heard from the people at Tendon Curve about here’s a problem we need to solve. Our technology can do it. We should do it if we can. And it’s what we’re working on right now will be released in the next month or so. I’m really excited to see that happen, that we have an idea of what we want to build and offer. But when it starts getting used, the, the users are going to tell you, by the way, this could be better. I’d like it to do this. And then we decide if we can do it. And then we do.

Bill Neumann: Nicole, from a, from the perspective of like challenges or pain points with eligibility verification, have you seen AI able to alleviate a lot of those or some of those and specifically what would they be?

Nicole Collard: Yeah, so I mean, our biggest pain point is the length of time it takes to verify members’ insurance. Our patients, they come in on Saturdays and the offices aren’t open and things like that. So it’s really alleviated a lot of that because it’s very quick. We can at least tell the member, hey, your insurance is active. It looks like this is, we accept your insurance plan, all of that information up front, which is amazing. Because a lot of times on Saturdays, someone has an emergency appointment. where typical office isn’t able to verify them, they’re either paying out of pocket or they get turned away. And then some of the other pain points that we have is just Interpreting the data is always the biggest one. Every single payer portal says something different when it’s talking about, for example, a downgrade on a crown. They use different terminology and it’s really hard to train your staff how to interpret that information if they don’t have a wide range of knowledge. So AI really helps standardize that language across all insurances.

Bill Neumann: Dr. Wu, from a perspective of daily operations, can you talk a little bit about how AI fits into like from, let’s say from like patient check-in all the way to claims processing, can you talk a little bit about how that really helps enhance that, you know, that you really think about it from the patient actually coming into the office, checking in to, you know, verifying that and processing that claim?

Dr. Greg Wu: Well, like Nicola said earlier, having that information readily available and quick, it makes it easier so we don’t have barriers to treatment when a patient comes in. Because when a new patient comes in or even an existing patient, is their insurance up to date and are they covered? Because otherwise, are we turning them away or are they turning the treatment themselves away? So there’s that workflow. And obviously we use AI with all the other things with Curve that Curve offers. We use, you know, Perl AI and we use, you know, voice to notes. So there’s like Bola AI. AI is all over. And so, All of the different AI out there allows us to be more efficient so that we can focus on the patient, which is what all of us dentists want to do is focus on our patients, not really managing paperwork and looking up insurance. And I went to dental school for, and I speak, I think I speak for all of the dentists out there that, you know, the insurance portion of it wasn’t something that we went to school. We don’t really understand. the more simplified and the more that’s easy for us to understand, it’s much more easiest for us to take care of our patients, which is ultimately the end game for us.

Bill Neumann: It’s certainly it’s not why you went to dental school. And it’s it’s certainly a big bottleneck. And I think probably a frustration point for both the person at the front desk, the clinician and certainly the patient. If if it takes too long or, you know, you can’t verify the insurance or something is maybe verified incorrectly. Right. And you have to go back later and try and, you know. have a conversation with the patient about payment.

Dr. Greg Wu: Well, isn’t that the patient’s biggest frustration? If a practitioner or the team member says, I don’t know, it’s like it’s much more. We want to confidently tell them, like, yes, this is your plan and this is what’s covered. And this is what we expect for a payment from their plan. Sometimes I would say to them, you know, I’m not sure. And so that’s what’s hard for patients to hear. And it’s also equally hard for the team and everybody.

Bill Neumann: Right. And sometimes the patients don’t know what they’re covered for. Right. They know they have this plan. Here’s my card. And that’s that’s about the extent of it. And in a lot of cases. Yes. Talk about automation and really the way the front office team is handling insurance inquiries, has that changed at all, Dr. Wu?

Dr. Greg Wu: So I say that again, I

Bill Neumann: Yeah. We talked about AI and how from the inquiry standpoint, if you can maybe take a look at the way things are now and maybe go back four or five years, what are some of the changes you feel like from a front desk team perspective, how those inquiries are being handled? really time, right? We’re not spending, they’re not spending as much time on that. I mean, is the eligibility, I mean, we feel like we’re getting, we’re verified, are the verifications better? Are the outcomes better?

Dr. Greg Wu: Yes, thanks for bringing that up. I think there’s more confidence that we’re getting data. That’s the bigger thing. Five years ago, it was like, is this right? Is this the right amount? Is this the right amount of benefits remaining? Have I maxed out of my insurance? Sometimes it’s like, okay, well, we’re not sure. We have to verify that, but you know how much time that takes. And then obviously, we’re a multi-specialty practice, so Our patients rarely go out to outside referrals, but there was a point in my time when we would refer a patient to get a root canal or an extraction and their insurance is used in another office, then we don’t know how much benefits they have remaining and how accurate is that. So all those are headaches in itself. So with the eligibility and the verification being close to real time, that’s actually a game changer for practitioners, patients, and staff

Bill Neumann: Nicole, at TEND, are you measuring the improvements? Like, is it there? Are you kind of doing benchmarking? What are the results that you’re seeing?

Nicole Collard: Yeah, so we do a lot of quality assurance when it comes to insurance verification, specifically because we tend to really focus on price transparency. That doesn’t mean that they’re not gonna have a bill after they get treatment or things like that, but we wanna be as open and upfront as possible with our members on how much they could potentially owe for a treatment. So we’ve done a lot of QA from our manual side of things, like how accurate are those verifications? And then with AI and all of the other data streams that we have, how accurate it is. And we aim to be 75% accurate across all verifications for all of our members. And we usually maintain that. Previously, when it was being done manual, it was closer to 75% accurate. So you would miss a lot of waiting periods, age limits, things like that. It could really leave a large balance for a member or a patient that they weren’t expecting.

Bill Neumann: Dr. Wu, I’ll ask you this question. Have you seen any changes in patient satisfaction or staff morale when it comes to implementing AI? And I know we think about AI and a lot of, especially from a staff perspective, like, oh, no, I’m going to take my job away, or it’s something new that I have to learn. So there tends to be some apprehension there. But talk a little bit about, you know, staff morale and patient satisfaction.

Dr. Greg Wu: So it’s funny that you bring that up. That was the running joke, right? We all know that movie Terminator 2 with Skynet. They’re like, Dr. Wu, are you buying Skynet and replacing us? And I said, no, I’m trying to make your lives easier because I think the technology can help us. So it’s not dentist versus AI. It’s dentist plus AI. We’re going to team up with this. And there is no Again, at the end of the day in dentistry, we’re in the people business. We take care of people and there’s compassion and those are things that AI cannot replace. But there are mundane tasks that we can obviously delegate to AI to make our workflow easier. AI should allow us to just take care of patients. That’s what we want to do and all of their needs. There are things that AI will never replace because I can’t see AI all of a sudden having empathy and the ability to talk to strangers in a kind manner, because that’s what we went to, like I said earlier, that’s what I went to dental school for, is to take care of people.

Bill Neumann: Yeah, I think that’s important. I mean, there may be some empathetic voices, but whether that’ll translate AI voices or whether that’ll translate over, I don’t know about that, especially when it comes to dental care, where you have a good percentage of patients that are fearful. I don’t think AI is going to be able to solve that problem. I think you do need a person to handle that. Nicole, unexpected benefits, anything that you’ve seen from this implementation, things that you weren’t necessarily expecting but have occurred?

Nicole Collard: I wouldn’t say anything that we weren’t 100% expecting, but I mean, our patients are now really used to being able to just walk in with their insurance and know that it can be verified within 10 minutes. So we actually have seen an uptick in same-day with their treatment and getting same-day treatment done because we have a full, broken-out eligibility. We also do specialty in our office, so if someone needs an extraction and we have an oral surgeon on staff that day, because we have a more comprehensive verification, our members feel more confident getting that treatment right away.

Bill Neumann: Yeah, I think that’s a really good point as we, you know, we’re in this age of, you know, everything should be delivered now. The Amazon, we get it in two days and then, you know, you go and you go to a dental office and trying to figure out, you know, well, how much am I covered for or I have to wait for this or I need a referral or, you know, the crown’s going to come back. We are in, we’ve been, There’s this different expectation now. Everybody expects things yesterday at the speed of Amazon. And it’s nice to know that now people will know exactly what their insurance is what they can take advantage of. And I think also some of the other technologies out there, we have diagnostic AI, you’re doing crowns, you know, in the office. So I think dentistry is finally catching up to what consumers expect. Speaking of that, let’s kind of move forward and we’ll talk about future perspective here. We talked about AI and technology just evolving so darn quickly. And I give you Dr. Wu and Nicole a lot of credit for just keeping up with it all because it is really, it’s such a challenge. I think Dan and Troy, I’ll ask you this question. What are you working on at Dental Exchange? Troy talked about this, that there’s something coming out in a month. So you’ve got a lot of things that are evolving there. Can you give us a little perspective on what’s on the horizon right now for Dental Exchange and what Tend and Emerson Dental and the others can expect?

Troy Andrews: Yeah, one of the things I’m really excited about is what we’re calling LG8. So our product is designed to get you, you know, 80 or 90% of everything that you need to create your treatment plan. But there’s always going to be one or two things that’s unique about how does Aetna handle this or how does MetLife handle this. that someone’s going to have to call the payer. So we’re working on a proof of context, a proof of concept product with a partner that uses an AI agent to make those telephone calls, which sometimes can take an hour or more of just maneuvering through the phone to get to a person and then asking a person. And the AI agent that they have developed does have a very empathetic voice, but a human being. But it is amazing to watch this process that is so tedious for a human to get taken care of by a, by an AI agent. It’s called Eligibly Complete. We should have it ready to go in Q1. It to me is an interesting way to kind of blend everything we’ve been talking. How do you interpret the data that’s different in a payer? How do you get the most up-to-date information? That maximum benefit discussion is a great example. That’s something that could change minute to minute. And only by having the most current, accurate information do you know exactly what to tell your patient. So our goal is always how do we get… How do we get to the things that a human doesn’t want to do? Not replace them and not take away their jobs, but like you said, free them up to do something that they would rather be doing than sitting on hold with Aetna.

Bill Neumann: Dan, Troy did a great job of explaining some of the innovation that you’re working on at Dental Exchange, eligibility complete that you’re working on. I’ll ask you, Dan, what do you think, just from a perspective of AI in the benefit verification space, what do you see, what does the future look like in the next maybe year or two?

Dan Feimster: Yeah, I’ll elaborate. It is an extension of what Troy is sharing around. We are working across a network of payers and providers. And I mentioned earlier around our focus around enhancing financial transparency across the entire network. And so we intend to continue to bring the benefit information to the point of care as much as possible. So, that means at the chair side where you might be having a conversation, Dr. Wu, on a treatment plan, can we give you the confidence that we are offering a nearly real-time pre-adjudication where it’s a marriage between the eligibility information of what’s covered, what’s not covered, but where they’re at in the deductibles or where they’re at within the claims processing rules that a payer might have. And that for us, we have a very good conversation. with your patient around what’s covered, what they can offer you, not have a surprise bill at the end of it, and have them still there in the practice where they make the decision, yes, let’s proceed with this. And so it supports both the practices from having the conversation that is right for the patient. It processes easily on the back end and helps with the payment cycle as well. And so we’re going to continue to advance that clinically driven revenue cycle bringing information to the point of care at the time, the right information. And so, that’s part of what will continue to evolve over this next year.

Bill Neumann: That’s great. I’ll ask this question to Nicole and Dr. Wu. How would you like to see things evolve? What are some things that you’re really looking for that you hope are in development or you’d really like to see? Nicole, we can start with you.

Nicole Collard: Yeah, so a big focus for us is the second half of insurance verification is kind of how I think of it is we have our upfront verification that we get from AI and it’s great. And then the claim actually processes. And I think Everyone knows that they don’t necessarily process the same way that you would have expected them to, like there’s a downgrade that you didn’t expect, or they require very specific clinical guidelines for a specific code. So it’s almost the second half of that verification is now we actually know how the claim paid. So going forward, we’ll have an even more accurate quote for our members and estimates because we know even though the insurance doesn’t say they’re going to do this, they do do this. And making sure that Anyone that has that insurance going forward will not be blindsided by anything. So we can have those honest discussions about payment with their treatment up front, as opposed to now I have a bill in the mail I wasn’t expecting.

Bill Neumann: How about you, Dr. Wu, anything that you’re you’re looking forward to seeing?

Dr. Greg Wu: Yeah, I was going to say the same thing is that there’s always those unique things that certain insurances have special rules. I would like to be able to know ahead of time, hey, almost an alert. And equally, obviously, there’s the verification, but also when the claims get submitted and paid, integrating it with the software so that, you know, it’s actually allocated automatically. So, you know, I mean, I’m a big Star Wars geek, so I can, my imagination can go wild with what AI could possibly do, but, you know, I have to be realistic one step at a time, right? But I would just imagine in the future I can just push a button and everything will be taken care of.

Bill Neumann: Well, since you’re both early adopters, what advice would you give the listeners? We’ve got a lot of emerging dental groups, some solo practitioners, even some large groups out there that maybe haven’t adopted A.I. or are considering using some type of A.I. eligibility tool. Dr. Wu, any advice for the listeners?

Dr. Greg Wu: Those that were worried and didn’t want to be the first one, don’t worry. I was that person. So now you don’t have to be the first. Now you can be the second or the third. And, you know, you have someone you can ask like, hey, when you integrated, did you run into this? Because when you are the early adopter, you don’t have that person to talk to saying, hey, when you integrated, you know, curve and when you integrated, you know, eligibility plus, did you run into these issues or did you, did you have any, I can be that person for you because you don’t have to worry about being the first one.

Bill Neumann: That’s great. Nicole, any advice?

Nicole Collard: Yeah, I mean, I would say the same thing. Because we were early adopters, we didn’t have anybody to lean on, but I feel it’s expanding in the dental industry, right? There’s so many products that are coming online to make your practice easier and more streamlined. So there are resources now out there that you can ask and say, this is a concern I have. And there are people that will jump in and say, well, this is how we fix that problem or if we had any changes in process, there are people to lean on for that. And then the other part is, it’s a tool. It’s not really to replace your workforce. It’s really just to help you put people where they need to be to talk to your patients. That’s the most important thing. So getting that admin burden off of your team members is just, it’s a tool. It’s really important and it’s gonna make your employees happier and it’s also gonna make your patients happier because they’ll get more face time with your treatment plan coordinators and your doctors and your hygienists.

Bill Neumann: Thank you, Nicole and Dr. Wu. So we wrap this up here. I’m going to final questions around, you know, learning more about dental exchange. So Dan and Troy, if somebody is interested in learning more about eligibility AI, or they want to talk to either one of you or both of you, what’s the best way for them to kind of take that next step, knowing that they’re not going to be an early adopter? Dan?

Dan Feimster: Well, the easiest way is there’s ways to connect with us directly on our website. The other way is we’re happy to provide contact information. You can reach out to us.

Bill Neumann: Yeah, absolutely. And you can, we’ll put all that contact information, the URL to just directly go to dentalexchange.com and get a demo. Or if you’re, I know you’re both on LinkedIn, so you can find, I’m sure find you and contact you there on LinkedIn. We’ll get the email addresses. set up. And if, Nicole, if somebody wants to learn, we might have somebody that’s interested in maybe learning more about TEND, they might have a practice that they want to maybe potentially partner with TEND, or maybe they’re looking for a career opportunity. What’s the best way to learn more about TEND?

Nicole Collard: Um, yeah, they can reach out to me on my LinkedIn, which, um, or we usually just go to the HelloTend website. So it’s HelloTend.com. Um, and then on the bottom, we have like a learn more section, so you can click onto that. And then there’s a couple of contact emails on there as well.

Bill Neumann: Excellent. Dr. Wu, how do people get in touch with you?

Dr. Greg Wu: So same thing, I’m on LinkedIn as well. And obviously you can also contact me through my office, my office emails on the website. And I’m happy to be a resource for those that are interested in learning about AI and, you know, someone who’s usually the first one to jump first. So, you know, that way you don’t have to be. Excellent.

Bill Neumann: Great, great conversation. I learned a lot. I’m sure the audience did as well. And we’ll make sure that we put all those website addresses, LinkedIn addresses or handles, and you’ll be able to just click in the show notes and reach out to anybody that you need to. Great discussion on AI and revenue cycle management and I’m sure this won’t be the last discussion because in 90 days, it’ll change pretty drastically. I’m excited to, you know, hear about this eligibility complete when that’s launched. And just it’s great to, you know, we’re getting there, right? You know, this process that shouldn’t be as complicated as it is. And sometimes I think the insurance companies like it that way, but we’re going to try and make it a lot less complicated. And I know dental exchanges is leading the way. And thanks to early adopters like Nicole and Dr. Wu for really being vulnerable and taking advantage of this. these great solutions and not being afraid. And thanks everybody for listening or watching this podcast. Again, without you, we wouldn’t have great guests like we have here today. Until next time, this is the Group Dentistry Now Show.

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