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Company focus

AKASA

What factors are contributing to the recent 30% increase in processing time for AKASA's automated prior authorization system?

Prepared by NextSprints

15 mins
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Data Analysis Problem Solving Technical Understanding Healthcare Technology Insurance AI/ML Root Cause Analysis System Performance AI Optimization Healthcare Tech Prior Authorization
Product Management Root Cause Analysis Question: Investigating healthcare AI system performance degradation

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.

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 system change. Has there been any significant update or deployment to the prior authorization system in the last 30-60 days?

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.

  • Considering user segments, I'm wondering if this is affecting all providers equally. Are we seeing this 30% increase across all provider types and specialties, or is it concentrated in specific areas?

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.

  • Thinking about the metric itself, I'm curious about the definition. Has there been any change in how we measure or calculate processing time recently?

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.

  • Considering external factors, I'm wondering about any regulatory changes. Have there been any new healthcare regulations or payer policy updates that might be affecting our authorization process?

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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NextSprints

Updated Mar 29, 2025