Dental Financial Planning: Practice Capacity and Patient Growth - Part 2

In this episode of The Dental Boardroom Podcast, host Drew Phillips breaks down how to fully use your dental practice’s provider and facility capacity to drive growth. Building on the last episode, Drew shows how to measure your true capacity, find gaps in your schedule, and use simple strategies to close those gaps.

Running a dental practice is about more than filling appointments—it’s about making every chair, provider, and day count. Drew shares a step-by-step approach to understanding your practice’s numbers, improving scheduling, and creating predictable growth.

Key Points:

• Learn how to calculate your true provider and facility capacity.
• Find and close the gap between your current schedule and full capacity.
• Improve reappointment and reschedule rates to grow your patient base faster.
• Discover scheduling changes that can take your practice from $900K to $2.6M revenue.
• Plan hiring and future growth based on clear, predictable data.
• Use technology to re-engage patients and fill seats.
• Focus on making one location highly profitable before expanding.

If you’re a dental practice owner or manager, this episode shows you exactly how to grow smarter, not harder. Instead of adding more locations or spending more on marketing, learn how to maximize the resources you already have. This clear, practical guide will help you create a profitable, predictable practice and reach financial independence faster.

Transcript:

Drew Phillips: [00:00:00] Welcome back to another episode of the Dental Boardroom podcast. My name is Drew Phillips, and I'll be the host of today's episode. This is the second episode in our two-part series, all geared around provider and facility capacity, which we went into great detail last episode, and on today's episode, we're going to.

Translate what our provider and facility capacity is and compare that to the amount of patients that we have on our schedule today, and that delta that we're trying to remove through patient growth on our schedule net of attrition and all of the variables and data points that we need to not only know and be able to calculate well, but also set processes up.[00:01:00]

So that our day-to-day services in the office can give ourselves the best chance at creating an optimal relationship between all of them while simultaneously creating a more predictable environment around the movement of patient growth, net of attrition. And once we get great processes in place to optimize these items, now we'll get to a place where we can start to.

With a high degree of certainty, be able to estimate how many patients we're adding the schedule this month, the next month, and so on and so forth. And that delta of what our current provider capacity is relative to the number of patients on schedule will start to be able to equate in the form of time how long it will take us to resolve that deficit or that gap.

And depending on the length of time that it takes us to resolve that gap [00:02:00] may be an indicator that we're too overstaffed

or that we need to look at more creative solutions at rounding out that gap faster because that gap will reveal itself on your profit and loss statement. A higher labor margin as a percentage of of revenue. And the only way to really improve labor margins other than decreasing wages or re reducing headcount is to fully optimize the utilization of that provider's capacity with the patients that we have predictably on their schedule.

And when we pair those two things together, your labor margins will be as favorable as they can be. Based on your clinical treatment style and the conversions of those exams into treat doc doctor clinical treatment. [00:03:00] So going back to last episode's example, we have an eight operatory practice that currently has two columns of hygiene four days a week, and we been through the different variables that ultimately translate to the provider and facility capacity in this example.

And just as a refresher, this practice has eight patient hours a day, so a nine hour day with an hour for lunch. It has a 10% cancellation and no show rate that goes unfilled with other appointments. Their patient base is 20% perio and they schedule new patients for two hours in the hygiene chairs. They block those two hour new patient appointments, one per day per column of hygiene or two new patient appointment blocks per day of the week.

So on a 17 [00:04:00] average working day per month, which is a four day work week, we can expect those two new patient blocks to generate 34 new patient opportunities, assuming that they get filled.

And when we put it all that together, that translated to each hygiene hygiene column, being able to facilitate four and a half people per day on average per column, and on a 17 working day month. That's 153 people that those two hygienists together can facilitate

and for the entire office, it allows for them to be able to see 900 existing patients in their hygiene schedule annually or every six months. When we look at the [00:05:00] number of patients on the schedule at the time of this exercise, at least in this example, there was 600 people already on the schedule. So we're trying to fill the gap between the 600 patients that are on our schedule and the 900 patients that the current provider mix allows for in the hygiene chairs, which is also an equivalent to the number of exams that we can theoretically expect the office to generate.

On an annual basis. And so when we take that delta, that gap of 300 people, now we're gonna get into the segment of what goes into patient growth attrition, and are we actually adding or losing patients month over month when looking at the scheduling schedule? And the next set of variables that goes into that calculation are as follows.

We have new patients, pretty simple. Every new person coming in in that month, we have [00:06:00] the existing hygiene patients that are scheduled for that month. We have the cancellations and the no-shows for the new patients and the existing patients that are scheduled for the month, and we have those that go unfilled and the amount of those that get rescheduled for a future date, all of those are important.

And then with both within both the new patients and the existing patients visits, we have our reappointment rates, our in-office reappointment rates, we'll call them, and how well we perform in those areas will dictate how hard our front office team has to work in between those recall visits in order to reengage and get those patients back on our schedule.

Also the lower or more unpredictable that those reappointment rates are for new and existing patients [00:07:00] will either make this exercise going forward easier and more predictable, or harder and more volatile to account for, and the more predictable that we make them, even if they're not where we want them to be.

In terms of patient growth month over month, at least we know once. Optimized any new patient growth that we achieve or obtain, whether it's through marketing or through better scheduling practices, we know that those reappointment rates will hold true and we can account for that patient growth and what it would add in terms of how many we're growing on the schedule net of attrition very, very simply, and in that example, or in this example, we have.

34 new patient seats that we've created on a consistent basis. One two hour new patient appointment per column of hygiene per day of the week. 17, working days per month. [00:08:00] And if we start these reappointment rates using sort of the law of averages that I've. Been able to, uh, to get through my client experiences before we start to pay attention and really implement best practices in those areas.

We're gonna see about a 45% reappointment rate for new patients, anywhere from 65 to 75% for existing patients. And then once those patients are not reappointed and they go into we, what we'll call the unscheduled limbo queue. What percentage of the time do we bring those unscheduled patients back before it's been 18 months since their last visit?

And what percentage of those patients do we bring back after it's been 18 months or more since their last visit? Because when we put all of that together, that will tell us. To the patient level if we're growing or losing every month. And so at 45% new patient reappointment, 75% existing patient [00:09:00] reappointment and 45% rescheduled rate with, you know, less than 18 months since their last visit when they don't reappoint the chair.

And then 15% for new patients. And then lastly, 3% for those that make it. 18 months or more without their visit. So just using that, those figures coming outta the box, it not rocket scientists to see that the longer and the more time that they go without being reengaged and added back to our schedule, the higher the likelihood that that we have lost them.

Indefinitely. Now, obviously there is real attrition even in the most optimized practices because people move, unfortunately people do pass away. There are legitimate reasons why we will lose patients. Um, and that's okay. We account for them in our benchmarks that we strive to achieve and why we don't set out to be perfect at a hundred percent across the board.[00:10:00]

And when we have those metrics coming outta the gate. What the numbers are telling us is that of the 34 new patients that we receive, we're only adding five patients to our schedule month over month, net of attrition on average, and to fill those 300 seats to round out our provider capacity. In this example, today, you take the 300 divided by five, and it would take us close to five years.

56 months before those providers are at full utilization. It's a long time.

Now, if I were to expand this idea a bit or this example a bit, and take our new patient experiences that are scheduled for [00:11:00] two hours per column, per day of hygiene. Move them to an overflow chair that would be in part run by an assistant for the x-rays and the hygienist doing the probing and perio charting so that we know before we ever do a cleaning, whether or not they are a perio patient or a prophy patient.

If we take that concept for a moment, knowing that those two hour blocks, if we remove them out of that chair, would be given back to existing patients. Now our Delta is not 300 anymore because now our new daily provider capacity is 6.5, not 4.5. And so our office's capacity is now 1,310 hygiene patients a year, not 900.

And the delta between the 600 people on our schedule today and the 1,310 that we now have capacity for in this new idea. [00:12:00] 710 and that 710 divided by the five that we're growing by is 132 months or 11 years. So between five and 11 years, depending on how you schedule those new patient experiences with the reappointment rates and rescheduling rates that people have more often than not before, they pay more attention and detail to them.

Now let's use both of those gaps of time, five and 11 years, and let's see how those improve once we change our reappointment rates to more optimal levels. So for new patients, I would love to see this at 75%. Even if we have to do three or four restorative appointments before that new patient comes in for hygiene, I still would love to see their hygiene appointments scheduled for whenever that future date is going to be.

And if we keep the idea. At the office level that no matter what, any patient comes in for that day, [00:13:00] every patient leaves with their next hygiene appointment scheduled, and we create processes around that or intertwine that idea with the current processes that you have. That alone tends to lead to pretty swift and fast improvement in those metrics, and it's something that you would like to track with the people that are responsible for them.

To hold them accountable, I'm gonna create that accountability with them. So 75% is what the new patients would go to in an optimal environment in between 90 and 93% for the existing hygiene patients. So if I put that at 90% to start, and then our reschedule rate, so before it's been 18 months since their last visit goes from 45 to 60%, because there's less people in that queue less.

Time that needs to be expended to reengage with that amount of people. And so our realization rate actually improves quite a bit. And if we can layer in some decent [00:14:00] technology with online scheduling and automated touchpoints to get them reengage without human elements, that can actually go up as high as 70 to 75%.

Not a reason not to reappoint strongly in the office, but still nonetheless, the added extra benefit that technology can. Can provide because it doesn't need to sleep nearly as much as, as, as us humans do. So it's 60% up from 45, and then our reactivation rate, which is people that haven't been in 18 months or more, that goes from one a month to seven and so on the same 34 new patients a month instead of only growing by five, we're growing by 30, and the time that it takes for us to solve.

For the, the expanded six and a half patients a day per hygienist instead of four and a half is less than two years, 23 months to be exact. And for, for the del, for the [00:15:00] gap that we had with the new patients in there, it went down from five years to six months. Now for some, even with the expanded definition of two years with the cha, the positive change to patient growth.

Some may say that that's too long. Well, before, if we were filling those 34 spots pretty consistently with new patients in the way that we were structuring it, and now we move those to an overflow chair, maybe we open up the online schedule, whatever, but at least we empower the front office team to book new patients and emergencies in that chair to the tune of, you know, three, maybe four a day.

Now we've also given the office the chance. For their brand, their goodwill, their hard marketing dollars that they spend to actually translate in a growth in new patients. So whether or not you intentionally block out your hygiene schedule for 90 minutes or six, or for two hour blocks, [00:16:00] right? Or you put them in as they come in regardless, hygiene, openings, or hygiene capacity for new patient scheduling.

Whether it's now or it's in the future, we will always present a roadblock and a cap in terms of what you can fully realize. And so unless you have a good idea of what your new patient availability is stated, and you're intentional about the creation of those seats, you could have the greatest marketing, the greatest brand, 9,005 star Google reviews, and you're only gonna get as many new patients as you've created the room for.

And so at a minimum. If you take that away and parlay that with, you know, some of your maybe marketing frustrations. So many of my clients have been in practice for so long that when we just make slight tweaks to increase the new patient seats on a, in a given month basis, the majority of those new seats are, are, are filled [00:17:00] the very next month.

Because it wasn't a lack of phone calls, it wasn't a lack of great marketing or branding, it was purely a lack of not having a seat. To call a home and the time in which it took to get them in too long, and so they call elsewhere, right? And so this is how we can, you know, lock in more people that are calling without spending any more dollars on marketing.

It's almost, it's pretty rare that we have a marketing problem. More times than not, it's a scheduling issue. And so not only are we giving more seats back to existing patients and increasing the hygiene capacity and the number of exams that we can accomplish over there. But we are also potentially going from 34 new patients to maybe 50 with a single provider, 45 with a single provider to upwards of 60 to 70 if we added a second doctor.

And so if I make, if I turn 34 into 50 and keep the same retention and reappointment rates in place that we had already optimized, [00:18:00] now it's only taking us 16 months. To fill those 710 seats or two months to fill the seats in the old scheduling system, time is money. Money is time. And how we control for that and estimate that we'll ultimately all go back to, to, to units of time.

And so if we continue on this idea, great. So we've, we've solved for the provider capacity that we have today. We solve for the increase in provider capacity that we created by small, subtle, uh, uh, scheduling changes. And now we turn our focus back to the other capacity element that we talked about in our last meeting, which was facility capacity.

And in an eight chair practice with six and a half patients that we can see after moving new patients out of the chair and into an overflow chair per column, per day. Well now we're able to [00:19:00] see. 2,620 patients, or call it 2,600, once we fill out the other two columns of hygiene to get to four total columns a day, four days a week.

And if I take that 2,600 patients, that it would be at that point of maximization, less than 600 patients that we have on schedule today. That's 2000 patients that we would need to add. In order to round out both the provider capacity of today, but also the future facility and provider capacity of tomorrow when we have four chairs a day instead of two.

And if I take that 2000 delta and I divide it by the patient growth at 50 new patients a month, with all of those retention measurements optimized, it would take us just under four years. In order to build out the entire facility [00:20:00] capacity that we have available and our revenue per patient per year in this example has not changed.

So we are gonna at, at 2,600 patients on schedule at that point times our a thousand dollars per patient per year. Now this practice is doing $2.6 million of revenue as opposed to the 600 patients at a thousand dollars that it's doing today. Or the 900,000 of original provider capacity that we had before we move new patients out of their chairs.

So we went from $900,000 of potential revenue to $2.6 million of facility capacity revenue in less than four years. And along that four year timeline, we will be adding thousand dollar nuggets to the tune of 42 net patients worth of growth month after month. So if we take that 2.5 million and we know that the only changes to the overhead structure would've been two additional [00:21:00] hygienists, 'cause we already had two of them, it would've been two more assistants to facilitate the second doctor that would've needed to serve the new two columns of hygiene that we added.

And it would likely be.

Two more front office people to get to four total front office people to bring that whole vision to life. So we added two front office people, two hygienists, and two assistants and a doctor. So of that increase of $2.5 million, 1 million of it is going straight to the bottom line. And so now this practice went from basically breaking even at 600 patients a year on schedule to making a million dollars before taxes a year.

And that's just the power and the margin potential of maximizing the [00:22:00] facility capacity of any location. For any dental practice, which is another main reason why I would never advocate for someone to open up more locations until they fully realize the utilize utilization and created the systems and processes around that location to make that very streamlined and predictable.

And once you've built that predictable engine, if you're so entrepreneurial that you are still not done from there, great, that's when the next location makes sense. Removing this, this idea that DSOs or whoever pays more for more locations, what they pay more for is higher ebitda and higher, the highest level of EBITDA achievable in any, in any particular business, is gonna be maximizing that facility capacity again.

Right? Um, so higher EBITDA is the major key there. And more providers in a single location, as long as they're fully utilized, is also. Away that DSOs are gonna give you that higher multiple [00:23:00] because they have less concentration risk in any single provider at that point. And so you can accomplish a lot of those objectives while not spending your time going between two or three locations and really applying those, that logic to one and making that one really, really great.

But also a part of this idea is that once we predictably understand growth. On at a, on, you know, monthly patient's net of attrition. We're not gonna wait until the data says that we've run outta room to add the next provider. 'cause all we're gonna do in that sense is hire a provider with no schedule built out and then have to build the schedule around them.

And so every provider hire at that point would be l leading with losses, not profits. So if we know that we're, that we have a super predictable schedule here. Or predictable growth rate, I should say. Well, we know for every 200 patients [00:24:00] we have

one full day of hygiene, one day per week, when you think about it on a six month term basis. So if I take those 200 patients that we know we need to fill one day divided by 42. What we're essentially saying is every four months, we need another day of hygiene. Between four and five months, we need another day of hygiene until we finally fully round out everything.

And so instead of waiting four or five months, what this is so helpful for is five months out, six months out, we open up that extra day of hygiene so that as these new patients are coming in, in our overflow chairs, as these patients are reappointing in our existing hygiene chairs, that we're creating permanent hygiene seats.

Six months when they need to come back for their recall. 'cause otherwise, what we're doing is we're trying to fit, you know, a thousand people into [00:25:00] 800 seats in the future. Somebody doesn't have a seat. So it's not just about channeling growth, but part of the way that we have great retention is by opening up that future schedule before we even have a provider to serve it.

Six months out in advance so that when we get a month away from that day that we've created, we've got six, eight, maybe 10 weeks of that schedule already prebuilt. So when we hire that hygienist to come in day one, they've got a profitable runway of six to 10 weeks. And every week, every subsequent week, we're building out during that six to 10 month period where we're already profitable, and we can apply that same logic to every position.

In the office. Every 700 patients that we add to our system, we need one more front office person. Every 700 patients we add, we need another assistant or fraction thereof. Now, it's not always the easiest thing to do to hire for one day a [00:26:00] week or two, or even two days a week, right? Sometimes part-time people in that sense are hard, but we are okay and we are happy to hire ahead of the curve.

And for me and my clients, that curve is 18 months or less. And so if I find somebody that needs two days instead of one, and I know that that day is gonna be solved for that extra day that they need is gonna be solved for in six months, I'm okay doing that. Right? And we'll still be profitable in the way in which we open that schedule ahead of time in that, in that effort.

And so again, going back to that unity economics of what one patient means. In terms of the number of assistant hours and hygiene hours and doctor hours and supplies and labs, and everything that's in your ecosystem can be tied back to that singular unit of measurement, which is a single patient. And when we understand the way that those single units grow, evolve, expand, contract [00:27:00] in a predictable way, we can make every single scaling decision profitably.

We can open up that schedule before we need that action so that we don't have a situation where we're adding people to the system without a permanent seat in the future. And so our likelihood of retaining them and being able to hit those optimal, optimal measurements and retention are that much easier and stronger to believe and get behind.

Thank you guys. For coming on me. Coming on this little mini journey of how volume and capacity and patient growth can be refined and channeled for the future development of your business, and to create a predictable timeline around the inflection points that we need to make critical decisions so that we're flying through the day and month with clarity and [00:28:00] transparency and not having to make decisions.

Based on gut feel, reaction, and we can continue the momentum in a meaningful and intentional way from the time that you start to the time that you hang up, that handpiece all in the spirit of getting everyone to the ultimate goal, which is financial independence and how we tie that financial independence back to the operational data that ultimately then manifests into the profit loss, the cashflow statements, and the balance sheets.

And the more CP, A driven metrics, they all are interrelated. They all have to be considered and optimized to one another. Thank you again. Until next time.