What caused the sudden spike in failed sample collections for Color's pharmacogenomics testing service last week?

Introduction

The sudden spike in failed sample collections for Color's pharmacogenomics testing service last week presents a critical issue that demands immediate attention and thorough analysis. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this could be related to a recent change. Has there been any update to the sample collection process or kit in the past month?

Why it matters: Recent changes often correlate with sudden performance shifts. Expected answer: Yes, a new collection kit was introduced two weeks ago. Impact on approach: If confirmed, we'd focus on the new kit's design and user instructions.

• Considering the specificity of "failed" collections, I'm curious about the failure criteria. Could you clarify how a failed sample collection is defined in your system?

Why it matters: Understanding the exact definition helps pinpoint where in the process the failure occurs. Expected answer: Samples are considered failed if they don't meet volume or quality standards upon arrival at the lab. Impact on approach: This would guide us to look at either collection issues or transportation problems.

• Given that this is a spike, I'm wondering about the magnitude. What's the normal failure rate, and what percentage increase are we seeing?

Why it matters: The scale of the problem influences the urgency and scope of our response. Expected answer: Normal rate is 2%, we're now seeing 15%. Impact on approach: A significant increase would suggest a systemic issue rather than random fluctuations.

• Thinking about user segments, I'm curious if this spike is uniform across all demographics. Are there any particular user groups more affected than others?

Why it matters: Segmentation can reveal whether the issue is universal or specific to certain users. Expected answer: The spike is more pronounced in first-time users over 60. Impact on approach: This would lead us to investigate factors specific to this demographic, such as kit usability for older adults.