Reducing No-Shows 73% with AI Scheduling

No-shows cost the average dental practice over $150,000 per year. Multiply that across twelve locations and you are looking at nearly two million dollars in lost revenue — not counting the downstream effects on staff scheduling, patient outcomes, and provider morale. One of our clients decided to fix this with AI, and the results were dramatic.

The prediction model

We built a model that scores every upcoming appointment on a 0–100 no-show risk scale. The inputs are surprisingly simple: historical attendance for that patient, day of week, time of day, appointment type, weather forecast, and days since booking. Patients booked more than three weeks out with a history of cancellations score high. Same-week bookings from reliable patients score low.

Tiered intervention

The score drives a tiered reminder system. Low-risk patients get a single text confirmation 24 hours before. Medium-risk patients receive a text at 48 hours and a follow-up call at 24 hours. High-risk patients get an additional reminder at booking plus a waitlist-swap offer if they want to reschedule. All messages are sent through a HIPAA-covered messaging platform — no PHI in the SMS body, just a generic "you have an upcoming appointment" with a secure link for details.

The results

Over six months, the no-show rate dropped from 22% to 6% — a 73% reduction. The clinic recaptured an estimated $1.4 million in annual revenue and reduced overtime costs from last-minute schedule scrambling. Staff satisfaction scores improved because providers stopped sitting idle during no-show slots.

The takeaway: AI scheduling is not about replacing your front desk. It is about giving them better data to act on.