Introduction
The recent 15% drop in successful alerts for Viz.ai's CT triage notification system is a critical issue that demands immediate attention. This analysis will systematically investigate the root cause, considering both internal and external factors that may have contributed to this decline. We'll follow a structured approach to identify, validate, and address the underlying issues while keeping in mind both short-term fixes and long-term strategic implications.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes could directly impact system performance. Expected answer: Yes, there was a minor update to the image processing algorithm. Impact on approach: If confirmed, we'd focus on the update's impact and potential rollback.
Why it matters: Helps identify if the issue is systemic or localized. Expected answer: The drop is more pronounced in certain regions. Impact on approach: We'd investigate region-specific factors if the drop isn't uniform.
Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: No changes to the definition or measurement process. Impact on approach: If changed, we'd need to recalibrate our analysis based on the new definition.
Why it matters: External changes could indirectly impact our system's performance. Expected answer: CT scan volumes have remained relatively stable. Impact on approach: If volumes changed, we'd need to factor this into our analysis of the alert drop.
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