Introduction
The recent 30% increase in processing time for AKASA's automated prior authorization system is a critical issue that demands immediate attention. This performance degradation not only impacts operational efficiency but also potentially affects patient care and provider satisfaction. In this analysis, I'll systematically investigate the root causes, generate data-driven hypotheses, and propose a strategic plan to address the issue.
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 often correlate with performance issues. Expected answer: Yes, there was a major update. Impact on approach: If yes, we'd focus on the changes made; if no, we'd look at gradual degradation factors.
Why it matters: Helps identify if it's a system-wide issue or specific to certain user groups. Expected answer: The increase is more pronounced in certain specialties. Impact on approach: If concentrated, we'd investigate those specific areas; if widespread, we'd look at core system components.
Why it matters: Ensures we're comparing apples to apples and not seeing a false positive. Expected answer: No changes to the metric definition. Impact on approach: If changed, we'd need to recalibrate our analysis; if not, we can proceed with current data.
Why it matters: External factors can significantly impact processing times. Expected answer: No major regulatory changes. Impact on approach: If yes, we'd need to adapt our system; if no, we focus more on internal factors.
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