Should I Adopt a New Technology or Treatment Workflow? by Dr. Keith Nicholson

Part 1: Operations frameworks that quantify and demystify curiosity

by Dr. Keith Nicholson

As orthodontists, we’ve benefited from analytics and key performance indicators (KPIs) for benchmarking and tracking practice performance. KPIs enable us to be data-oriented. A natural evolution is to be data-driven by synthesizing comprehensive practice data to empower workflow optimization and business forecasts. We can apply operations and finance concepts to our specific office setting for customized practice solutions.

Practice management has become increasingly complex as we aspire to deliver excellent patient care and service while harnessing efficiencies. Many features of running a practice are interrelated, so it’s valuable to forecast how changing one lever may impact other practice variables. This can be achieved with a comprehensive model that is customizable and interconnected. This holistic model has versatile applications to inform critical decisions about technology, service mix, staffing, and more.

In this series, I’ll showcase how a holistic model may strengthen clarity around practical questions that we confront as orthodontists. I’ll use a baseline practice to illustrate how business frameworks could improve practice performance. This practice has one doctor working three clinical days per week, 46 weeks per year, supported by four assistants and one treatment coordinator, with 429 case starts per year. Since the baseline practice may not reflect your specific office dynamics or profile, the conclusions reached in each article should not be taken as universal answers. The purpose is to introduce prescriptive tools to augment your managerial leadership. This first article explores whether to adopt new technology or treatment workflows.

Processing time
Processing time (PT) is the time required to complete an appointment for a given patient. PT or related metrics can have many definitions, so it’s worth clarifying this term. For the context of this analysis, PT constitutes both value-added time (VAT) and non-value-added time (NVAT). VAT is productive chair time. NVAT encompasses activities such as writing a chart note, turning over the chair, and sterilizing the instruments. The baseline PT inputs in this analysis represent both VAT and applicable NVAT.

Acquiring accurate data inputs is paramount for these operations formulas to reveal constructive outputs. The data required for these computations can be culled from patient management software reports with a light bar or analogous tool that documents the patient journey at different stages. However, if this is not being documented accurately, then a time study analysis can be conducted to record the patient journey and PTs for each appointment type. At a minimum, the collective expertise of the office team could likely generate reasonable estimates.

Will digital indirect bonding unlock practice growth?
Should you integrate digital indirect bonding (DIB)? In reality, this decision is multifactorial. This article will focus exclusively on profitability as the decision factor. Nonetheless, it should be noted that there may be other compelling reasons to offer DIB, such as being a tech-forward brand, enhancing the patient experience with less chair time, or ostensibly improving treatment outcomes.

DIB is purported to save chair time insofar as it decreases the bonding time, need for bracket repositioning, or total appointments. Our baseline inputs will reflect two key features of DIB: time-saving benefits and increased expense compared to a conventional direct bonding system.

Contribution margin and service mix
To answer whether implementing DIB will improve profitability by bolstering capacity, we’ll first evaluate the contribution margin (CM) of different services. CM is defined as the revenue generated minus the variable costs. This metric can be calculated for various treatment offerings to investigate which deliver the most value per case, per appointment, and per minute of PT.

Treatment recommendations depend on the diagnosis and on patient preferences. Secondary to these parameters, the profitability of each procedure can modulate the scope or distributions of treatment offerings. Therefore, examining the CM of different services can provide clarity about service mix or participation in insurance plans.

Table 1: Contribution margins per case, per appointment, and per minute of doctor processing time. CMs are calculated for each case type.

Table 1 summarizes the CMs of three case types for our baseline practice. Of course, the CMs could be modified by changing the case fees, suppliers (lab and supplies expense), or staff compensation structures. The abundant features of the holistic model are interconnected, so we can forecast the impact on CMs of changing these variables. Nonetheless, those inputs will remain fixed for now so we can focus on the potential efficiencies of DIB that derive from its time savings per case. Specifically, in our baseline practice example, the total doctor PT for a DIB case is 119 clinical minutes, which is 27 minutes less than that of conventional braces.

DIB’s CM at the case level is lower than that of conventional braces since DIB has a higher lab and supplies expense. However, DIB delivers a higher CM than conventional braces at the appointment and PT levels. These insights suggest DIB may confer advantages for profitability, depending on existing office capacity and bottlenecks. If DIB had a lower CM for all categories, including at the PT level, then our curiosity could stop here, as the takeaway would be that DIB erodes profitability regardless of its time-saving benefits.

Notably, the highest CMs are conventional braces (case level) and aligners (appointment and PT levels). Since DIB and aligners often require nonclinical time for case setups, I also ran an analysis that factored in the administrative time for these tasks.

Since DIB yields a higher CM at the appointment and PT levels than do conventional braces, two important insights are the patient growth required to break even and the potential patient growth without requiring more patient care time. For these computations, I’ll focus on the subset of patients (conventional braces) who would most likely be candidates for DIB. Using the CM values in Table 1 ($5,490 vs. $5,237), the required patient growth to achieve breakeven profitability is 4.8%. I should emphasize that this growth would only be applicable to the cohort of patients (here, conventional braces) who are candidates for DIB. Per Table 1, the doctor PT per case is 119 minutes for DIB vs. 146 minutes for conventional braces. From this efficiency, DIB could theoretically enable 22.7% patient growth without requiring additional patient care time. Since this number exceeds the breakeven profitability calculation, DIB could improve your bottom line without adding patient care time.

Table 2: Implied utilization for the treatment coordinator, assistants, and doctor.

We should acknowledge that models aren’t prescient enough to precisely forecast the future. There is variability in how a particular system would interface with your workflows. Therefore, a constructive tool is a sensitivity analysis that illuminates the expected change in a dependent variable at different values for independent variables. Recall that our baseline expectation is that DIB will require an aggregate of 27 minutes less doctor PT than conventional braces. A sensitivity analysis tested DIB’s CM per minute of doctor clinical time at different levels of aggregate doctor time savings per case and of lab and supplies expenses per case. Across DIB time savings of 10 to 50 minutes and lab and supplies expenses of $250 to $650 per case, DIB’s CM per minute of doctor time ranged from $37.16 to $56.76. It fell below that of conventional braces (about $37.55 per minute) only in the least favorable scenario: 10 minutes of time savings with $650 in lab and supplies expense.

Now that we have evidence that DIB is capable of boosting profitability by expanding patient throughput, the next question is whether capacity is a current constraint in the practice.

Capacity, implied utilization, and bottlenecks
Will a time-saving system actually address the bottleneck constraint and unlock capacity? The bottleneck dictates the capacity of the overall practice, and office capacity governs the upper limits of productivity. Capacity is the number of patients per unit time who can be seen with a designated number of resources. Improving capacity can raise profitability and reduce patient pain points.

For this section, we’ll investigate capacity and implied utilization (IU) as a function of our valuable resource, the office team, which can be grouped into front office, treatment coordinators, assistants, and doctors. Capacity may be constrained by other resources such as office space or the number of operatories. I’ll address this in the next article using Little’s Law.

There are several ways to evaluate whether an office is at or near capacity. The lead time between scheduling an appointment and appointment availability offers some insight. However, a more sophisticated way is to compute IU. IU is the demand placed at each resource relative to its capacity.

A target IU is 80% to 85% to optimize productivity yet allow a buffer for variability, which is foundational to health care services. Variability can derive from both patient and office factors. Examples include patient punctuality, patient compliance in the chair, case complexity, staffing shortages on a particular day, broken brackets, or ill-fitting appliances. If IU is greater than the target range, then variability can create workflow disruptions and lead to long wait times for some patients. If IU exceeds 100%, then your office is unable to meet the demand within the designated time. Lastly, the team group with the highest IU is the bottleneck.

Using the baseline caseload of 681 active patients, I estimated the expected number of appointments per year, then computed the patient demand rate based on the average available patient care days per year and hours per day. For the baseline practice, that works out to approximately 56 patients per day, or about seven per hour.

Table 2 illustrates the IU for each team group. The doctor has the highest IU at 96% and is therefore the bottleneck resource. Also, the doctor IU is above our target IU range, so this is a cogent reason to alleviate the bottleneck (decrease the doctor’s aggregate PT). Strategies can be broadly categorized into delegation, automation, and outsourcing. In this baseline practice scenario, integrating DIB would be one mechanism to offload the bottleneck. Other options may be a retainer program, a bigger emphasis on aligner treatments, or an increase in the doctor’s clinical time, among others. Moreover, even if IU calculations didn’t justify DIB integration on the surface, DIB could be a worthwhile investment if you aim to scale back clinical days. These business frameworks are agile enough to offer insights that fit individualized goals and questions.

Conclusion
Operations and finance frameworks are a paragon of data-driven management. They can be unified into a comprehensive model that empowers you to examine how changing different levers, sometimes contemporaneously, impacts efficiency and productivity. The key is customization: Use inputs and a model design that capture your practice numbers and workflows.

Additional Tables

Keith Nicholson, DDS, MS, MBA, is an orthodontist and published author who has been active in various domains of orthodontics. He has owned a four-location private practice, served as part-time faculty, and earned an MBA in finance from Wharton. As a consultant, Nicholson is passionate about creating value for patients, teams, and practices. Leveraging his dynamic background, he partners with peers to unlock their potential and deliver customized business solutions. He applies data-driven strategies to optimize operations while delivering excellent care. Additionally, Nicholson supports dentists and dental specialists with practice transitions as a consultant at PMA Practice Transitions.