What caused the sudden 30% increase in appointment cancellations for NYU Langone Health's orthopedic department last week?

Introduction

The sudden 30% increase in appointment cancellations for NYU Langone Health's orthopedic department last week is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the department and the broader healthcare system.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product ecosystem, user journey, and relevant metrics. From there, I'll generate data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this could be a seasonal trend. Has there been a similar spike in cancellations during this time in previous years?

Why it matters: Helps distinguish between cyclical patterns and anomalies. Expected answer: No similar trend in previous years. Impact on approach: If seasonal, we'd focus on capacity planning; if not, we'd investigate recent changes.

• Considering user segments, I'm curious about the patient demographics. Has there been a shift in the age groups or conditions of patients booking appointments recently?

Why it matters: Different demographics may have varying cancellation behaviors. Expected answer: No significant demographic shifts noted. Impact on approach: If shifts exist, we'd tailor solutions to specific groups; if not, we'd look at broader systemic issues.

• Thinking about recent changes, have there been any updates to the appointment booking or cancellation system in the past month?

Why it matters: System changes could directly impact user behavior. Expected answer: Minor UI updates were implemented two weeks ago. Impact on approach: If changes occurred, we'd scrutinize their impact; if not, we'd explore other factors.

• Regarding performance metrics, has the definition of 'cancellation' changed recently, or have there been any changes to how cancellations are tracked?

Why it matters: Ensures we're comparing apples to apples in our data analysis. Expected answer: No changes to cancellation definition or tracking. Impact on approach: If changes occurred, we'd recalibrate our analysis; if not, we'd focus on actual behavioral shifts.