Findings Report — Appointment No-Show Analysis
Muthoni Veterinary Clinic
Prepared for: Wanjiku Muthoni, Owner and Head Veterinarian Date: [Date of report] Data period: [Start date] to [End date] (18 months)
Executive Summary
[2-3 sentences summarizing the key finding. State the overall no-show rate WITH its 95% confidence interval — not just the point estimate. Name the visit type with the highest no-show rate. State whether the trend is stable or changing. This section is what Wanjiku will read first and possibly present directly to her staff.]
Key Findings
[Bullet list of 3-5 findings. Each finding should state the metric, the value, and what it means for the clinic. Include confidence intervals where relevant. Example structure:]
- [Finding about overall rate with CI]
- [Finding about worst visit type]
- [Finding about client tenure patterns]
- [Finding about temporal stability]
- [Any additional notable pattern]
Detailed Breakdowns
By Day of Week
[No-show rate for each day (Monday through Saturday) with confidence intervals. Note any days that stand out. Present as a table or list.]
By Time Slot
[No-show rate for Morning, Afternoon, and Evening with confidence intervals. Note any time-of-day patterns.]
By Visit Type
[No-show rate for Consultation, Vaccination, Dental, and Surgery with confidence intervals. Highlight which type is worst and whether the chi-square test confirms the differences are statistically significant. State the p-value and its interpretation in plain language.]
By Client Tenure
[No-show rate for New vs Returning clients with confidence intervals. Note the practical implication — if new clients no-show more, what might that mean for how the clinic handles first-time bookings?]
Temporal Trend
[Describe the monthly no-show rate trend over the 18-month period. Is the rate increasing, decreasing, or stable? Reference the trend chart. Note any months with unusual spikes or dips if present. State the overall assessment: is the problem getting worse?]
[Reference: see trend chart in the notebook]
Recommendations for Next Steps
[2-3 actionable suggestions based on the findings. These should be practical steps Wanjiku could consider, grounded in the data. Examples might include targeting reminders for high-risk appointment types, adjusting scheduling for time slots with elevated no-shows, or tracking new metrics going forward. Keep these brief and grounded — the data shows patterns, not causes.]
- [First recommendation]
- [Second recommendation]
- [Third recommendation]