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CHALLENGE:
One person predicting clinic demand for 25 locations
The dental clinic operates across 25 locations, each requiring the right mix of doctors, practitioners, and support staff to deliver a seamless patient experience. Ideally, every clinic would run at full capacity every day, but that wasn’t the reality on the ground.
Daily patient footfall varied significantly across locations, and staffing decisions depended entirely on predicting how busy each clinic would be. This responsibility fell on one dedicated team member who was single-handedly managing this complex task daily. She was responsible for anticipating which clinics would see higher patient volumes and required additional staff, and which clinics would see low footfall, where closing the day could help reduce operational costs.
After our first successful implementation with the company, they shared this challenge with us, and we immediately got to work on how to bring accuracy, predictability, and data-driven confidence to their daily staffing decisions. The goal was clear—develop a solution that could reliably forecast the number of patients expected at each clinic every day.
SOLUTION:
Building a data‑backed framework for smarter clinic operations
Jumping straight into a solution would have been similar to working manually—with only the information right in front of us. To increase accuracy, our approach is always to take a step back and think about step 0 before diving into step 1.
To accurately predict appointments, we first needed a reference point: What did a typical day look like in the past year? And what factors influenced appointment patterns?
We pulled data from their scheduling tools, insurance systems, patient history, and clinic operations, and put in the integrations and governance needed to ensure the data was clean, reconciled, and reliable.
A six‑month forecasting engine to guide clinic hours and staffing
With this foundational dataset in place, we moved on to addressing their core challenge—predicting appointment schedules. We took the consolidated, governed data and projected expected patient volumes for the next 180 days. Using machine learning and predictive forecasting, the Azure app displayed both scheduled appointments and predicted demand in calendar and table views. This gave the teams a more intuitive way to understand upcoming clinic activity and make informed decisions.
In addition to highlighting scheduled appointments, the model continuously compared them with forecasted demand to recommend clinic open days. This shifted the entire operating rhythm. In the first review, the app flagged 7–8 “should-open” days at specific clinics. On one of those days, the model predicted nearly 30 appointments, even though only one was scheduled. This gave the team the confidence to proactively open that clinic for the day, assign providers, and capture demand that would otherwise have been lost.
Preparing clinics two days in advance with intelligent patient briefings
One of the dental clinic’s strongest values is ensuring that every child receives a personalized and stress‑free experience, and when they shared this aspiration with us, we immediately knew we could use the same step‑0 data foundation to support it.
With the right data already integrated, we built a use case that would help staff prepare for each patient before they even walked through the door. Two days before any scheduled appointment, every clinic now receives a detailed morning huddle PDF. This document outlined all upcoming appointments in a clear, clinic‑sorted schedule that shows which provider will be seeing which patient and at what time.
The pdf transformed a standard visit into a thoughtful experience. The huddle PDF includes insurance and eligibility details, so front office teams can address coverage or outstanding balances without last‑minute surprises. It also brings in behavioral indicators and clinical risk levels, including the caries risk score based on AAPD guidelines. This allows dentists to quickly understand which children may need extra attention due to recent cavities or ongoing oral health risks.
What truly elevates the patient's experience, is the inclusion of notes from past visits—small but powerful details like a child being sensitive to cold water or feeling anxious about X-rays. These insights give the clinical and front‑office teams everything they need to tailor the appointment, whether that means warming the water, preparing a comfort‑first X-ray approach, or simply offering reassurance before the visit begins. By enabling clinics to prepare proactively and personally, the dental clinic can deliver the kind of care that aligns perfectly with their mission: making every child feel seen, understood, and cared for.
RESULTS:
Improved accuracy, better prepared providers, and happier patients
We built two core models for the dental clinic, an app that predicted patient appointments and an auto‑generated morning huddle PDF that helped personalize each patient’s experience.
With predictive forecasting guiding daily decisions, the responsibility of estimating patient footfall shifted from one individual managing 25 clinics to a data‑driven system. This aided informed decisions about when to open clinics, how to adjust staffing, and where to allocate resources, resulting in smoother operations across all locations.
The morning huddle PDFs further enhanced daily preparedness. Clinic teams could walk into the day fully informed, anticipating each child’s needs and tailoring their approach with intention. This has led to smoother appointments, reduced stress for young patients, and a more coordinated, confidence‑building experience for both families and staff.
