104: AI in Dentistry: How NexHealth Is Automating the Patient Experience

Welcome back to another episode of the Dental Boardroom podcast. I'm your host, Drew Phillips and today we are continuing our special series on AI in dentistry, where we dive into how emerging technologies are transforming the way we run, scale and innovate in dental practices. Joining me today is A guest from NexHealth, one of the most forward thinking companies in dental tech. NextHealth is redefining patient communication, online scheduling, real time EHR integration and automation in ways that are actually usable today and not five years from now. They're helping practices stage their data in a way that unlocks the full potential of opportunities that AI has to offer by allowing practices to work smarter and deliver a more modern patient experience. Kyle Johnson is the head of growth at NexHealth and I'm excited to have him on the show today to share how their tools are impacting real dental teams across the country. Kyle, welcome to the show.

Thank you. Yeah, great to be here. Looking forward to it.

Likewise, man. So, Kyle, to get us started, could you just share maybe how you found your way to NEX Health and what your journey with them has been like thus far?

Absolutely. So I joined Next Health January 2020. I think I was employee number 11 brought on board to take us from seed stage to series A. And I had been in healthcare technology for about four years at that point, so I was familiar with the space, you know, as a company called Patient Pop that is now merged into a company called Tebra. So I was familiar with the space. And when Al, our co founder and CEO, reached out to me, what really stuck out was, you know, he wasn't just trying to make another piece of software to do online scheduling or appointment reminders. He had really zeroed in on the data integration challenges into the practice management system and was and was laser focused on solving that. So that's ultimately what kind of really piqued my interest. This was a huge, meaty problem to solve and that is kind of what brought me in. And here I am five and a half years later. I can say that I.

Confidently see myself here another five years still working on this problem. It's a big one.

It is a big one. And AI is a very, you know, far reaching term and there's a lot that goes into that scope. Maybe you could kind of help set the stage today for our listeners in terms of, you know, what Next Health is doing to kind of facilitate that next the future of AI within dentistry and kind of the things that you guys are trying to unlock as it relates to those topics.

Yeah, I think that's a great place to start. AI can mean a lot of things to a lot of people right now, especially as kind of the whole topic blows up.

But I think one of the fundamental things, no matter kind of what your perception of what AI is and does, it needs information. It needs inputs and outputs, right? From like patient data, practice schedule data, to do anything. And so long before AI or LLMs were a household acronym, you know, back In, I think 2016, you know, our co founder, CEO alone grabbed a summer job in the Bronx at a medical practice. He's ecw, and I think within a week or two was just overwhelmed with how many tedious, time consuming, repetitive tasks it took just to keep the office moving, you know, just to keep the practice on the rails. And I mean, this is a tech savvy college student who's thinking to himself, there's gotta be a better way. Like I gotta be able to fix this within a couple weeks, right? And just quickly ran into wall after wall trying to get access to ecw. And I think like that personal experience is what kind of formed his.

Understanding of the data challenges within the healthcare space and led to eventually what became NextHealth. So that is fundamentally the problem that NextHealth was founded to solve is removing these barriers, these walled gardens across all these different electronic health record systems and practice management systems.

To make it easier for dentists to be able to, you know, deliver the patient experience that they want to get better clinical outcomes, to make it easier for patients to pull all their data into a single place. So that is kind of our point of view. And if you can't do that, then it's really difficult to slap AI on top of it and magically kind of solve some of these problems, these administrative problems that, that kind of still plague the front office today.

You know, what does it mean though, when you say data integration challenges? Right. I mean, one of the things that we do like to do here is kind of distill it down to the most basic format that we can do, you know, and so if I, if I know nothing about data at all, what is.

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That all mean yeah, so I mean if you think about it, the U.S. government, you know, within the context of American healthcare like they did a great job of getting providers onto, you know, off of paper and into the digital record systems. What they didn't really incentivize was.

How you could use these systems. I mean, if you think about it, the primary input output is like your eyeballs reading information off a screen and your hands, you know, typing or clicking on things back into the system. That is a fundamental bottleneck in terms of trying to solve problems efficiently in an automated sense. And.

You don't necessarily need a sophisticated AI to see that there's a gap in your calendar at 9am tomorrow and then reach out to people that are on the wait list.

That's just good software. And the reason that hasn't existed. And I think the reason that AI seems really shiny in a space that has kind of been starved of good software to solve these problems is because.

You know, the software doesn't exist because it can't get access to your health record system to execute on those workflows. So you have to fill your front office with people to do all these things, proactively, reach out to people, chase people down for cancellations, you know, file paperwork, scan it into the system and it just piles up. And so that is. Does that answer your question?

I think, yeah, I think, yeah, for sure. And then, you know, in. So I think that to kind of go in a different direction slightly, you know, which, what, what I know of Next Health, which I've, you know, I'm a user of Next Health products. I've, you know, been very intimate in terms of the background information that you guys do and share with the different practice management software systems and how you guys pull data, read and write. Right. And I think that, you know, what you guys have done well, which is create these integrations with these practice management systems to be able to extract data. And then that data is now usable in very many different or a lot of different AI formats that other people could ultimately leverage and continue to build out their own version of what will ultimately be this sort of broader ecosystem of AI tools.

Yeah, so the fundamental challenge is that, you know, there's just, there's. There's literally hundreds of different practice management systems and EHRs in the country. They all have different ways of, you know, some of them allow complete open access and the integration problem isn't really there for them. I would say that's not the norm. A lot of them are very tightly guarded or difficult to work with. You have to have a business relationship in place first. So there's a lot of red tape. There's a lot of variation between systems. There's at the kind of lowest level when you actually start thinking about how they store and model that data, it all kind of can be different. So these are a lot of challenges for somebody that just wants to come into a space and try to solve a specific workflow. For a dentist.

It'S a huge amount of overhead to deal with as you're just starting up. And so that's kind of what the synchronizer that we built does. It sits on top of all of these different systems and it abstracts away all that complexity so that you can just come in and say, you know, is Operatory 4 available tomorrow at 9am for this type of procedure, no matter whether it's, you know, Dentrix or Eaglesoft or Ortho or Cloud or any of those. So that is, that's kind of the low level data problem that we solve.

Let's maybe look at some of the core functions that you guys are already solving for, which are, you know, really important ones.

Right.

We'll start with online scheduling. You know, as long as your scheduling templates are kind of configured in a way where you, you know, you have it built so where people are booking themselves, they're booking themselves in the right places at the right times in a very conducive sort of flow. Right. Which is, which is great. That's taken a pretty large burden off of the amount of phone calls that we have to facilitate. It's also created an environment where we're able to get more new patients on our schedule because we're not limited by the working hours of the day and the people in the front office, you know, having to take action to get them there. That's, that's, you know, by itself really wonderful. Assuming it's program properly, which your tool allows for very customized programming and so it's definitely very possible. But then when, when it starts to break down, not that your system is breaking down, but the process itself. And just in terms of the system limitations that exist today, like if I cancel an appointment, right. Or I have an opening, you know, that's while I can leverage the tools out there around online scheduling to sort of mass blast patients to fill a gap in the schedule. Right. I could easily see how AI tools could be more creative and sort of solve for that more manual process that leverages the technology to make their lives more palatable than traditional phone calls and text messages used to be. But it would be an interesting thing if the AI could read the patient data and somehow, you know, get comfortable with which patients are most likely to take these certain spots that are open and then cycle through those patients without as much human intervention that is required today. So anyway, I'm just kind of, kind of trying to look at what you guys have built and like those areas where you see AI, you know, enhancing your own tools that you already have as much as you are building that data platform to allow others to be able to come in a lot easier and do their thing.

Yeah, yeah, happy to expand on that. I think, you know, we, we obviously are very bullish on, on AI and, and are incorporating it into our actual SaaS production. We have taken probably a little bit more conservative approach. We're not Rushing in and trying to just slap AI on everything. Because I think that.

When anything is brand new and it's hyped, you want to be careful that you're actually introducing functionality that will deliver real value, solve real problems, and not just be an extra button that we can point to and say, hey, we did that. And so really the way we think about adding AI into our SaaS product is helping the person that's using our products, like the office manager that's logged in and chatting with patients or looking to fill gaps in the calendar for the next couple days to essentially help them do that workflow, that job to be done in fewer clicks. Really we're trying to think about how can we reduce the amount of clicks, the amount of time, the amount of mental overhead it takes to do all of these of jobs to be done that a front office manager would be juggling on a day to day basis. And so what that looks like so far is, you know, when somebody texts you through the next health product, I mean, we'll automatically suggest some responses that make sense for that type of question or patient comment. And we are in our marketing kind of campaign capabilities, we have the ability to, you know, use AI to generate text message and email content that has a high likelihood of converting and driving action, which I think can be a huge time saver. Not everybody is, you know, the marketing could be really challenging even when you're focusing on that full time. And so it can be daunting to sit down and think about, you know, how can I write like a great email here that goes out to, you know, 200 people? So those are the types of things we have AI in the product to help with today. And we are getting to the point where.

Will start. But I guess I'll clarify, a lot of those things are, hey, we think you should do this. And then the person says, yes, that looks good, let's move forward. I think we're getting to the point where we're introducing functionality that both us as the product creator and the person using the product will feel comfortable of removing those confirmation steps. Because we're still in this kind of world of AI where a lot of it's really good, but there's always, you know, there's not always, but there's often kind of this thing that pops up and you're like, I wouldn't have said that. And we want to, you know, we don't want to put our practices at our office staff in a situation where we create new problems. And I think we're getting to a point where AI is, is, is what I would call like, you know, trustworthy, if that makes sense.

Absolutely. But still, still, there's still checks and balances that have to be done on the, on the human element basis.

Right, but absolutely.

But I could, you could definitely see where it's moving though. It's trying to weed us out as, as quickly as it can be, I think.

And I think that's one of the big challenges, right, is this, you know, with, with traditional software, you would call it deterministic. It's like I tell it to do this. If this happens, then this happens. Like, you know, if I have a new patient, send them this reminder for tomorrow and that just goes out and it works. But that we, even with that kind of automation, I've seen our own customers during onboarding be a little apprehensive. You know, it's like, you know, like I'm about to turn on this automation and I hope it works like it does. It's supposed to. And I think that's kind of one of the friction points for AI and in the dental practice more broadly is it's even less predictable sometimes. Like you're, you know, generally speaking, it delivers great results, but it can be a little bit more opaque. And so I think that that's probably one of the challenges that anybody kind of, you know, developing on AI and in healthcare right now has to, has to consider and kind of try to address.

What are the things that NextHealth sees on the horizon for themselves in terms of, you know, obviously we talk, you know, preliminarily here about some things that you guys are working on more, kind of setting the foundation for probably bigger projects. But what are some things that you guys are trying to accomplish over the next year or 2 internally at NextHealth? Yeah, and this doesn't necessarily have to be AI specific, just anything in general, really.

Gotcha. You know, we're rolling out payments capability right now for dental practices where we can sync every single transaction directly to the ledger and we can attribute that to the right provider, we can attribute payment to the right procedure code. We make it really easy for practices to send out detailed statements that, that show contribution from the different payers and how their payment fits into that. And then physical terminals that sit in the office and you can collect cards that way as well. So really kind of a comprehensive payment solution. We're really going deep on the finance component of the front office. So I would say up until last six months, we have been really focused on a lot of the, the patient journey from discovery with online reviews to getting more of them to actually book with you with online scheduling, removing paperwork with forms. And right now I think like the big opportunity to really eliminate a lot of inefficiency and manual task and is, is with the payments piece and then making that available in our synchronizer to the developers as well. So you know, where that, you know, from a product capability standpoint it's the payments. And then from the synchronizer we're doing a ton of work to support more dental practice management systems for more medical EHRs, give those developers more access to those systems so they can develop, you know, they could solve new use cases and new problems. Those are kind of the two big things we have on the horizon over the next, I would say 12, 18 months.

And the payments piece, I mean that's a, is that a going to be a system that will allow like the patient ledger balances to be updated in the PMS sort of automatically when those.

Transactions are completed and yeah, in real time. So payment happens, it immediately reconciles into the ledger. You can log into NextHealth and you can, you have just an immediate picture of who owes what and why, how old the balances are. You have a lot of filtering reporting capabilities. And then we have like, you know, we, you can leverage our communication suite of tools to just, you know, message all the people that have a balance older than a certain age or for a certain reason.

And essentially eliminate the need to use things like mailed statements and collections.

Which is, which is a challenge. It's a challenge. And I mean it's, I mean there's. The, the majority of the dental market is still doing it that way, right? For the most part.

Exactly.

You're definitely seeing a big shift. I mean it's companies like you that are innovating on that, on that topic that is allowing that to be more digital and more real time. What, what are some challenges that you guys have run into on, on rolling this out?

You know, I would say it, we've, we've rolled this out to quite a few of our existing customers. So we, we didn't roll it out initially. Kind of go wide with it to the, the market that wasn't already using NextHealth and it's just, it's gone really well. There's the, you know, people get access to kind of this real time visibility into what their AR balance is and their, their eyes kind of get really wide and, and then we walk them through setting up. It's like well, do you want to send a message out to these people and ask them to pay? Some of them are like over a year old, the balances and there's a lot of apprehension or just kind of like I don't know if this is going to work. And by the end of the call, money's already coming in and it's showing up in the ledger. So I would say like it's been pretty smooth. And it's been smooth because we put a lot of work into this ahead of time. We've hired product and engineering staff that has deep experience in payments specifically. We've, you know, we've really tried to build out that expertise first and now it's, I think it's just educating the market. But like, hey, you don't have to, you know, fill 200 envelopes every month and chase these people manually. Like there's a better way to do it.

Now have you guys tried to quantify, you know, even just given your current suite of, of products and services that you guys offer, if you guys try to quantify the time saved?

We do, yeah. And it can vary, you know, based on what capabilities of the product people are using but, and how they run the office, of course, but you know, just, just between online forms, you know, digitizing and eliminating, you know, paperwork and patient intake and check in process, I mean that for most of the practices I talk to and we've got a number of video case studies and case study materials that support this two to four hours a day across dental and medical practices payments. You know, I've heard anywhere from 30 to 45 minutes a day, not having to reconcile payments all the way up to an hour or two and then with like our wait list automation and filling those gaps in the calendar automatically and preventing kind of the need to do lots of phone tag there it can be.

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An hour or two a day, depending on the, you know, the size of the practice and patient volume. So it really adds up for a lot of practices that's, you know, a thousand hours a year.

Oh, easily, easily. I mean just, yeah, the online scheduling, the forms, you know, the, the access to bulk messaging. I mean it's, you know, obviously it's gonna be relative to the practice size that you're working with, but I mean, in almost every office it' a full time person that you're ultimately saving. Not that we get rid of that person, but imagine all the good that they can do in the areas where tech hasn't really come in and made as impactful of a difference yet.

Exactly. Yep.

Creates a pretty cool experience from what I can see right now. Technology in general, AI included, it's, it's still pretty fragmented, right? I mean there's hundreds of practice managed software systems, there's you know, five, six really popular dental phone companies. There's kind of somebody working on each sort of segment. Right. How do you envision this fragmented, these fragmented providers sort of coming together, whether it's through, you know, mergers and acquisitions or it's through, you know, APIs. Like how do you see the future of, in maybe 10, 12, 15 years from now, how do you see all of these people that are doing an amazing job in their one to four different sort of verticals kind of coming together and being able to leverage the full horsepower of the scope of what technology and AI is trying to solve for.

It's a good question. Well, I don't have a crystal ball, so.

But you know, I think we could probably look to other industries where we've seen them mature more quickly than the healthcare space simply because there's just not this integration data problem. You know, I think a lot of people think that innovation in healthcare is stifled because of regulation. But you know, for a, for a new developer, complying with something like HIPAA is, is super straightforward compared to having just deal with integrating with, you know, 15 new EHR systems out of the gate. So, you know, I think what we look at and where I think this could be going is, is something kind of like Shopify what they've done for online e commerce. I mean, you think of Shopify as this online, you know, like kind of this online website company. If you want to sell something online, you like an online shop, you go there and fun at its core. It's essentially what it is. But, you know, you can. You configure your product catalog and you don't have to just push it to your website. You can deploy it to Amazon or Facebook or Pinterest. There's all these different channel, like your mobile app. Right. I kind of think of NexHealth becoming something like that where you configure your availability, you know, program your availability once, and then all the developers that build on top of the synchronizer can just leverage that. So you don't have to go through an onboarding process necessarily with, you know, nine different companies. They just know this is how your schedule works. This is how you, you know, this is how you want to fill your calendar, as an example. So I think that there's an opportunity to help kind of standardize, you know, not just, you know, we don't want to just facilitate the flow of information from one system to another. We also want to just make it easier for tools to plug in and start working without having to go through, you know, a week or two of onboarding and training for your staff. Because I think that's one of the big challenges is, you know, the front office is strapped. Even if they are using tools to improve their efficiency, there's, you know, there's a good, good talent is in short supply. People are. People are strapped, they're working hard, and it can be difficult to.

To set, you know, set time aside and add that additional tool. So where I see this going is, you know, Synchronizer helps kind of does more than just move bits from one system to another. We help.

Make it easier for technology companies to not only integrate with your system, but to get you up to speed faster. And in terms of how kind of these technologies come together, in terms of consolidation within the space, I mean, I definitely think we're going to see it. We were already seeing it. We're seeing companies like Weave make acquisitions. They actually just acquired.

One of the first successful seed sage developers on the synchronizer platform, Truelark. And so we've, you know, it's kind of fun to watch that happen where they pre revenue, they joined an Excel synchronizer platform they built. On top of that they scaled, they got acquired by Weave. I think we'll continue to see some of the bigger players in the space like Weave make those strategic acquisitions instead of trying to build those capabilities themselves. And.

You know, we'll definitely see a consolidation. I believe in that type of tech.

Yeah. I mean, unless there's a new way of sharing revenue that will emerge from this, which is very possible. No crystal ball. But yeah, M and A does seem to me to be somewhat likely. Just because, you know, the user experience being in one system as opposed to bopping around between four or five systems to get that full job done would be helpful. But in the short term, intermediate term, you know, to your point, you guys are basically like the Apple Store. You've created an ecosystem where people can kind of build on top of that information, make it accessible to end users, and then, you know, which increases the pace of innovation. And then as those people innovate and they become sort of, you know, have solved a problem to a point where it's usable, that's when they become a target. That's really cool about TrueLART though. So they, they, you, they kind of use your synchronizer, built their product and then they had a successful exit. That's wonderful. I didn't know that story until today, but that's really cool.

Yeah, we're really happy for. I'm really excited they're continuing to use the synchronizer. So I think that's, it's definitely a win for truelark and I think it's a good example of what we're hoping to foster more of within the space.

So if we have some entrepreneurial sort of. We have plenty of entrepreneurs listening to the show, dentists that own their own practices and entrepreneur by themselves. But just in terms of a think tank mindset, how would developers that are curious about solving problems in dentistry, how would they be able to get connected and sort of leverage the synchronizer that you guys have taken so much time to build?

Yeah, it's a good question. And you know, just to kind of reiterate a point you made there, we do see a lot of dentists that actually request access to the synchronizer and they do build their own solutions. We have, we've got one that I can speak to right now called Dentina, which I think is another great example of success on the synchronizer platform. I mean, this is this is a dentist who decided to make his own product 12 months ago, started building in March, so a little bit more than 12 months, and had a product ready to go to market in two months with support for 85% of the dental market, all the major practice management systems. And a year later, he's got 500 customers, which is just to put that into perspective. I mean, it took next health years and years, five plus years to get to that scale because we had to build all this stuff from the ground up. So it's really exciting to see that the way you get started, it's really easy. I mean, it's, you can, you can go sign up, you don't have to talk to anybody. You could just go to nextheld.com we have a tab at the top for the API and you can sign up for our developer portal, get an API key, you'll get access to a sandbox. You can start playing around in the sandbox for free and yeah, give it a spin. I would encourage anybody listening that is interested in solving, you know, problems within the space to give it a shot.

What about if I'm a dentist listening to this and I've always, and I have this great, grand idea. That would be wonderful. You know, I don't know anything about coding. I don't know anything about, you know, APIs or how do I get, you know, like, of, like, you know, low code, no code, sort of sources or options that these dentists can go to to express their, their minds freely on while leveraging your synchronizer.

That is a great question. Now, I will caveat this by saying I haven't personally tried doing this with our own API and I probably should to set some time aside this weekend, but there are some great options out there and I'm trying to. Man, I was trying to come up with the name of one that I was just taking a look at while.

You'Re pulling that up. You know, I see Instagram, you know, bits all the time and it's like, you know, AI is doing 70% of our coding now, you know, or whatever. It's like, well, if AI is doing our coding and we just funnel in the idea and we have the data to play with that idea, that seems pretty reasonable and doable. However, I know that it's not that straightforward yet. So.

Yeah, you know, I think, don't let any, like, you know, I think if there's a lesson to be learned, well, you know, it's, it's. Don't let anybody tell you no, the Amount of people that told Al when he was a college student he was going to drop out of College to start NextHealth and solve his data interoperability operability problem. I mean literally everybody under the planet was like, you shouldn't do that. Yeah, right. You know, there's, there's something to be said for, for conviction. I will say that the, you know, having experience with some of these low code or no code platforms, you know, you can definitely build a prototype it. But it's kind of like if I wanted to do dental work and I used without any experience in dental medicine and I use chat GPT to help guide me, it's like I might be able to be, I'd be dangerous, literally.

I might be able to intellectually know what to do. But there is, you can make a prototype. I would suggest that if you are serious and you do really want to build something that you, you work with a developer, you know, these, these low code tools can be really good for prototyping. It's different though once you push it into production and you have to support it with, you know, customers and real patient data and all that. So.

Absolutely. What's the sandbox that you guys have in there? I'm assuming it's obviously it's not real patient data in there, but it's. We're able to kind of let like imagining this sort of translation tab or translation sort of mechanism that you've got these different practice management softwares feeding data in different formats and that going through that translation and then creating a comm data set to be able to leverage. Is that, is that a fair way of describing that?

Yeah. So I believe.

Our, our sandboxes are open dental.

Got it.

And, but yeah, behind the like.

But, but fundamentally, yeah, like it, it, it will like the way that the data comes in and out of our API. Like essentially what you're connecting your application to. The, you know, the.

Everything is the same regardless of whether it's open dental or Dentrix or EqualSoft or anything else. And the entire idea there is, you shouldn't need to know, you know, how this system does the specific task or how they structure the data. We kind of abstract and normalize that at the API layer.

I think you answered that perfectly. So it is open dental that the sandbox is sort of kind of created upon. But ultimately if I build something on top of that, I can trust that when, when it connected to a Dentrix platform, it's going to pull in and my program is going to work all the same.

Exactly. Yep.

Beautiful. Beautiful. Well, awesome, man. And then what? Yeah, I mean, what, what are some of the things that you guys got going on that you feel would be great to share today?

Oh, man. Well, let's see. I mean.

We, I mean we're really focused on the payments piece. We've got a lot of exciting, you know, I've already touched on that. We've got some exciting feature developments there we're not done in terms of product development. Things like surcharge, like basically like passing the payment fees on to the patient. So there's a number of additional improvements there that are in flux. So I think that's cool.

Are you guys, you're gonna, you guys gonna bake that into your service offer, your software offering?

Yeah, that's, that's the plan is we'll make it an option. Obviously it's not going to be like on by default, but for practices that like, let's say they don't want to raise their prices, but they're feeling a little strapped from like, you know, the operational increase in price, this could be a potential way of, you know, protecting margin a little bit by just passing on the processing fees to the patient. And so we've seen. Sorry, go ahead.

I was just gonna ask, do you guys help with the patient messaging for that? You know, because I believe there's has to be a signature or something. Right. Or I'm not, I'm not that aware of the process, but maybe you could allude to that a little bit.

Yeah, I think that's a bit out of my depth as well in terms of that specific detail. Yeah, but I, but I do know that, yeah, we're working on kind of the details of that. There's been a lot of interest from that. The practices that we talk to. That's kind of top of the list of, of the request. And so that's, that's one thing we're looking at rolling out and then that, and then, you know, payment support for just more systems. So every dental system we support right now, we don't, we support it for just a, like eaglesoft, entrix and Open Dental and we want to roll that out to all the practice management systems we support. So that'll be coming soon.

Yeah. On that point, you know, obviously cloud based practice management software systems are increasingly, you know, wanted, I should say. I'm just curious. You know, I find that a lot of the great products out there, yours included, you know, they, while they have wonderful integrations with the core sort of three practice management systems, the cloud based ones Tend to give them a little bit of trouble. I'm just curious if that's a thing of the past and the user base can expect more integrations with cloud based platforms moving forward or what your just general thoughts are on that idea?

Yeah, that's a good question. And I think it's also worth pointing out right in kind of the evolution of practice management systems going from server to cloud, there's been innovation there and yet still they're very difficult to integrate with. So it kind of just reinforces the need for the synchronizer. We do support a number of cloud based systems like Dentrix, Ascend and those systems just work, you know, they work differently than a lot of our server integrations. And the decision to roll payments out the way we did was largely just to get the ball rolling with the systems that were easier for us to work with. But yeah, we have support for cloud based systems. We have a lot in the works to improve.

Coverage of cloud based systems and our capabilities there because it's definitely the trend and I think that will continue. We'll see kind of these on premise.

EHRs and practice management systems slowly die out, at least at the small business scale. You know, they're still going to be in like the large institutional kind of space, but I don't think anybody running a private practice really wants to deal with an IT closet. So yeah, right.

They are the future for sure. What makes them so difficult? I know that is slightly outside of your scope, but what has made the cloud integration so, so.

Oh, it's a good question. So the, if you think about it, I mean like, if you think about it in kind of simple terms, the, the server integration is easy because the data is literally just sitting there in your office.

And so it, you really have more control over it and of the data and who has access to it.

And when you're doing a cloud based ehr, you know, you're running that in your browser and that is not talking to a server in your office, it's phoning home. And so.

The access model is just fundamentally different. The location of the data itself is different. Now the ownership of the data and like from a legal perspective it's still your data as the practice, but from a kind of integration perspective it presents challenges because we essentially like as the synchronizer basically just needs to be running in your browser which is just a different architecture, it works differently than if you have like the actual server sitting in your, in your office. Does that make sense?

I can imagine. Yeah, no, it does. And I can imagine, you know, server like hardware servers were designed to be as connectable as possible, if that's even a word, whereas the cloud infrastructure was probably built to be less. Less. So. Yeah, yeah, no, I, I think that that makes sense completely.

Maybe just to crystallize it further. I mean, like if it's, if it's a server in your office, I mean, you can just install other things on your server. Right. But you can't go to Dentrix Ascend and say, hey, I like, yeah, no, wherever you're running my Dentrix Ascend, I want you to also run this program. They're going to say, absolutely not. So.

Right.

Yeah.

Because that, yeah, because that increases the amount of, you know, on site servers that they have to. Yeah. The computer forms, as they say. But yeah, server farms.

Yeah, yeah, yeah. So you give up, you essentially give up some control and access for the convenience as essentially the trade off. Yeah.

Something I ask everybody on the show is, you know, if you have any, you know, podcasts or just resources or talking heads out there that you, that you subscribe to, to kind of stay on the forefront of, of the next wave of dentistry and things that we're, you know, that we should be looking out for. Are there anything that you'd like to share on that front in terms of great content out there that you, that you subscribe to?

Oh, man, I, you know, I do like listening to the deo. Dental entrepreneurs. And I gotta say, that's a good one. Yeah. Probably over the last. Well, that's probably been the only one I've, I've been paying closer attention to recently. So I gotta admit I'm not maybe the best person to ask that question. But I do like the, I do like the deo. I think they do a good job and I do peruse. I don't know if they have a podcast, but I, you know, I think Dental Economics has, you know, good articles, good resources. Yeah. Focus on kind of the more business angle and entrepreneur angle there.

Well, Kyle, man, it's been a pleasure to have you on the show today. I really appreciate you joining. If there's any last words or that you'd like to share or how people can get connected with you. You guys, obviously nexthealth.com is a great place, I'm sure. But no, please drop any in anything that you'd like to. For how people can get connected with you again.

Absolutely. Yeah. I really enjoyed the time today. Appreciate it. Appreciate having me on. Happy to come back and talk.

Oh, we're definitely going to have to get you back.

Yeah, yeah. We got some exciting stuff coming up that I can't talk about yet, unfortunately. And I don't want to be a tease, but.

It'S kind of been five years in the works to get to where we're at today, and hopefully we can come back and talk about some of the cool partnerships that are in progress. I will say that, you know, if your front office is struggling, you know, with tedious, repetitive tasks, that's something that we can easily help them solve for. The ROI is clearly demonstrable and the, you know, the patient experience is, you know, clearly elevated as well. It's a win win for both the practice and the patient. And so to learn more, you just go to nexhealth.com, you can request a demo there. You can give us a call through our 800 number. Yeah, we'd happy to give you a walkthrough of the product and help you estimate kind of the impact it would have on your practice with a quick call. So that's what I would recommend. Yeah. And.

That'S what I got. Yeah.

Cool. Kyle, thanks again, man. Appreciate it. Until next time.