AI for Practice Management

New technologies aren’t just changing the practice of dentistry; they’re reshaping the business of dentistry as well. Practitioners and DSOs considering diagnostic and other AI-powered software should also be thinking about the ways technology can ease practice management and boost the bottom line. 

After all, becoming a dentist and operating a practice is costly, and most dental schools don’t cover the basics of small business ownership like staffing, lead generation, and reputation management. AI-enabled systems, when connected to practice management and patient communication systems, can help boost efficiency, personnel work-life balance, and growth for small practices and larger networks alike.  

Tomorrow’s scheduling today

Let’s start in the front office. Office managers and care coordinators aren’t just a pivotal point of contact for the customer; they’re a pivotal part of the business. They collect payments, book follow-up appointments, and ensure the dentist’s time is being applied efficiently. But the traditional manual chart audits, scheduling, recall and marketing process that practices employ generally result in suboptimal patient retention, lead generation, and chair usage.
With an AI boost, front office staff can:
Turbo-charge their daily efforts to bring more patients with real treatment needs into the office and more same-day treatment, leading to improved practice-wide patient health and better financial outcomes for the practice.

Roshan Parikh, DDS, former head of dentistry for Walmart and a strategy consultant for DSOs, has seen first-hand how practices that are using AI to make clinically-informed business management decisions are benefiting.
“They look at tomorrow’s schedule and see, Roshan is coming in at 8 a.m. He needs two crowns done but they we’re treatment planned for whatever reason. Because AI can flag that before the patient comes in, the clinical staff can be ready to deliver same day treatment – leave more time on the doctors schedule, make sure supplies are on hand.
Roshan Parikh, DDS, president of dntl bar and former head of Walmart Dental.
Without AI, the scenario that Parikh describes would have required a tremendous amount of foresight –– not to mention clinical insight –– on the part of the office staff. AI performs that work automatically. Naturally, the same kind of AI business intelligence software can also automate more the traditional chart auditing efforts that go into prep for patient visits, providing, at a glance, information on which procedures are scheduled, what’s been deferred, what’s already been approved by the insurance company, and how much time the practitioner typically needs to complete it.“

You know if the person who has the 12 o’clock appointment needs to get her crowns done today because her insurance terminates tomorrow and she’s on a fixed income,” Parikh explained.

Merrit Dake, CEO of Rock Dental Brands, a network of dentist offices in Little Rock, Ala., calls those “efficiency gains.” Dake said those gains lead both to better patient care and to cost reduction. “Very often people come back for something that was missed or they didn't have enough time that day and now it has festered into an issue.”

Optimized call lists that prioritize urgent cases can get patients the care they need before it festers while ensuring the dentist’s schedule isn’t complicated by the need to treat an unforeseen issue.

“You can win the day easier and with less brain pain using the data you already have,” Roshan said.

The back office, back in black

For high-level insights, when diagnostic AI is applied across a practice or a DSO’s entire patient population, then cross-referenced with a PMS, these systems allow practice owners to assess quality of care, make staffing and purchasing decisions, and adopt more strategic lead generation practices.
AI can, for example, see if a particular dental assistant is responsible for a majority of the inadequate digital impressions that result in restorations getting returned and remade. Equipped with that insight, the practice might arrange for a refresher bootcamp on proper intraoral scanner operation. Or, if the AI software detects a rise in patients with malocclusion or missing teeth, the practice might consider getting Invisalign-certified or bringing in an implant specialist one day each week.
“If you’re thinking about adding a periodontist versus an oral surgeon or an orthodontist, you can look at what percentage of your current active patients have missing teeth or proposed implants versus what percentage have malocclusion,” said Parikh.
In the future, those technologies might also allow new providers or clinical support staff to take on more responsibility, because technology is providing a guiding hand, said Dake. In some cases, hygienists or assistants might be able to do a simple filling, as some can in Arizona, lowering staffing costs for practice owners and plugging a talent gap. “I think the biggest issue right now is that there are not enough providers for the people,” Dake said.

When less experienced staff can take over routine treatments, costs are lowered overall, more patients are able to get care and dentists are able to focus on more complicated and more costly procedures, improving ROI on the providers delivering the care that most demands their expertise.

And just as call lists can be optimized to get patients with urgent treatment needs in the door before their conditions worsen, they can also be optimized specifically toward recalling candidates for higher-value treatment. A computer vision system linked to a PMS can surface patients who have been putting off big-ticket treatments––treatments that, thanks to AI diagnostic validation, insurance carriers will approve and patients can trust.

“The AI would already populate with some confidence what the pathologies are within the X-rays. I can look at these findings as a reference before I see the patient and feel very confident when I say, ‘You need two crowns and two fillings,’ that their insurance company is likely to agree,” Parikh said.
This is particularly true in conjunction with AI-assisted payer workflow. “The treatment plan has these blue check boxes where the procedure codes are and when the AI on the carrier side sees the X-rays, I can be pretty sure it’s going to see what my AI system saw and notify the carrier that the treatment is warranted, so I can tell the patients with a high degree of confidence that they’re not going to get balance billed. And naturally patients are much more likely to accept treatment when they know that their insurance is covering it. In a way, this takes a lot of antagonism out of the provider-carrier relationship: The treatment isn’t just recommended because I see it. The AI had verified it for both me and the carrier. So we’re all three sitting at the same side of the table.”
Not only do these clinically-qualified leads fuel high-performance recall and reactivation campaigns, they facilitate a steady stream of referrals to specialty office. Plus, when speciality offices employ these technologies, the referral stream can flow both ways––something that doesn’t frequently occur in the traditional dental care workflow. This builds goodwill among generalists and specialists that can increase the volume of new patients for both categories of providers.
With an AI boost, front office staff can:
While practice owners are likely to see the benefits of a productivity boost, practitioners who are not owners but rather are employed by dental practices, are likely to be skeptical about a metrics-led approach to dentistry. This is especially true if the practice is not clinician owned –– as is usually the case in corporate, DSO-led and larger group practices.  When an owner who has not sat knee-to-knee with a patient, introduces business-oriented solutions that encourage a bottom line, numbers-driven approach to patient care, even if the solution is driven by clinical data, there is likely to be pushback. But there doesn’t have to be. To get practitioners to warm up to AI-powered practice management, Parikh offers the following tips:
Start with patient-based metrics.
Start with patient-based metrics. While dentistry can be a lucrative career, most practitioners put patients, not profit first. Start with patient-centered metrics that focus on quality of care and satisfaction, like an NPS score used in marketing organizations, to engage dentists and show professional growth. And remember to stay positive: “It’s not a deficit model of ‘you’re not doing a good job,” said Parikh. “Adopting the technology and knowing the metrics can help you get ahead and further yourself.”
Build up data-driven productivity slowly.
Once practitioners are accustomed to keeping track of their performance, point to productivity as a benefit of best practices. “You can say, ‘You did these three things and look at what happened to your production?’ Or, ‘You saw what your last month’s paycheck ended up being. That’s because you’re more confident and able to provide better comprehensive care to your patients.” Particularly at DSOs where dentists’ earn a commision on completed procedures, practitioners are likely to respond positively when they also see a financial reward for the care they deliver. “Even if patient care is their first priority, when they see more pay, now they’re bought in.”
Have an open door policy.
Because AI is still novel and metrics-based performance tracking is new to the industry, dentists are likely to have a lot of questions. Host regular meetings where dentists can ask questions, raise concerns and feel more comfortable about adopting this new technology. Once they understand what they’re working with, “you get to a point where there is provider-backed adoption and it’s self-sustaining.”
Read Previous Post
Building ethical AI
04
Coming Next Month
Dental AI and Patient Care

Get Dental AI 101 in your inbox!

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Consent Preferences