Case Study: A Brossard Clinic Reduces No-Shows by 60% with AI

Bylaeka

Unannounced absences (no-shows) are expensive for clinics: revenue losses, schedule inefficiency, and staff frustration. A clinic in Brossard facing this problem implemented an AI solution to optimize its reminders and scheduling management. The results speak for themselves.

The Initial Situation: A Chronic Problem

In January 2026, Clinique Santé Plus in Brossard registered an 18% no-show rate on its appointments. This represented:

  • 150 lost time slots per month
  • An estimated financial loss of $12,000 monthly
  • Artificially long wait lists
  • Stress for staff managing last-minute cancellations

The traditional reminder system (phone calls and generic SMS) wasn’t effective enough. Many patients didn’t open messages, or received them too late to reschedule.

The Solution: Predictive AI and Personalized Communications

Laeka implemented an AI system that:

  • Predicts absences: By analyzing patient history (no-show profile, distance from office, consultation type), AI identifies at-risk appointments.
  • Generates intelligent reminders: Optimal timing, patient’s preferred channel (SMS, email, call), and personalized message based on context.
  • Suggests overbooking: AI recommends slots where slight overbooking can compensate for predicted absences.
  • Facilitates rescheduling: A reminder link can directly offer the patient the option to confirm or reschedule.

Results After 3 Months

Since March 2026, the clinic has observed a spectacular improvement:

  • No-shows reduced by 60%: From 18% to 7% in 12 weeks
  • Slot recovery: 90 additional appointments honored per month
  • Revenue increase: +$7,500 monthly (75% improvement)
  • Reduced administrative stress: Staff no longer manages last-minute calls
  • Patient satisfaction: 23% increase in ratings related to punctuality and proactivity

Testimonial from the Administrative Manager

“Before, we were reactive: a patient didn’t show up, we scrambled to fill the slot urgently. Now, we’re proactive. AI tells us: ‘This person has a 70% chance of not coming, offer them a confirmation.’ And it works. Our schedule is much more stable.” – Dominique Marchand, Operations Manager, Clinique Santé Plus

How AI Learns and Improves

The AI system continuously integrates feedback:

  • Each absence confirms or adjusts future predictions
  • Each patient who cancels or confirms enriches the model
  • Seasonal patterns (flu, holidays) are automatically detected

After 3 months, the predictive model’s accuracy reached 82% on no-show detection.

Impact on Care Quality

Beyond the numbers, this optimization brings real clinical benefit:

  • Slots are better filled, enabling better continuity of care
  • Less administrative stress frees up time for personalized reception
  • Patients who would have waited months now have faster access

Lessons Applicable to Your Clinic

If you have a no-show rate above 10%, a data audit could identify similar opportunities. Key success factors:

  • Quality of historical data (12 months minimum recommended)
  • Seamless integration with your appointment management system
  • Privacy compliance and PIPEDA conformity
  • Staff training on interpreting AI recommendations

Next Steps

A free audit of your appointment management can reveal similar inefficiencies. Book your discovery call to explore how predictive AI could transform your clinic. Book your 30-minute discovery call

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