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Company focus

Charlie Health

What factors are causing the increased no-show rate for Charlie Health's initial assessment appointments in the past two weeks?

Prepared by NextSprints

15 mins
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Data Analysis Problem Solving User Experience Digital Health Telemedicine Mental Health Root Cause Analysis User Behavior Healthcare Tech Appointment Management
Product Management Root Cause Analysis Question: Investigating increased no-show rates for mental health assessments

Introduction

The increased no-show rate for Charlie Health's initial assessment appointments over the past two weeks is a critical issue that demands immediate attention. This problem directly impacts patient care, operational efficiency, and the company's bottom line. I'll approach this analysis systematically, focusing on identifying potential root causes, validating hypotheses, and developing both short-term and long-term solutions.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might be a recent change in the appointment scheduling system. Has there been any update to the booking process or reminder system in the last month?

Why it matters: System changes often lead to unintended consequences in user behavior. Expected answer: Yes, there was a recent update to the scheduling system. Impact on approach: If confirmed, we'd focus on technical issues and user experience with the new system.

  • Considering user segments, I'm curious about the demographics affected. Are we seeing this increase across all patient age groups, or is it more pronounced in specific segments?

Why it matters: Different age groups may have varying reasons for no-shows, affecting our solution strategy. Expected answer: The increase is more significant in younger patients (18-25). Impact on approach: We'd tailor our solutions to address the specific needs and behaviors of younger patients.

  • Given the short timeframe, I'm wondering about any external events. Have there been any significant local events or health policy changes in the past month that might affect patient behavior?

Why it matters: External factors can dramatically influence healthcare-seeking behavior. Expected answer: No major local events or policy changes. Impact on approach: If confirmed, we'd focus more on internal factors and patient-specific issues.

  • Thinking about operational changes, has there been any shift in the assessment appointment process itself, such as duration, format, or pre-appointment requirements?

Why it matters: Changes in the appointment structure could affect patient commitment and preparation. Expected answer: The format changed from in-person to virtual for some appointments. Impact on approach: We'd investigate the impact of virtual vs. in-person appointments on no-show rates.

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Updated Jan 22, 2025