Introduction
Highmark's significant drop in preventive care utilization among members aged 50-65 is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our preventive care program.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Changes in member demographics could explain utilization shifts. Expected answer: No major demographic changes. Impact on approach: If confirmed, we'll focus on engagement rather than population shifts.
Why it matters: Data integrity is crucial for accurate analysis. Expected answer: No recent changes to tracking or reporting. Impact on approach: If confirmed, we can trust the data and focus on actual utilization factors.
Why it matters: Cost barriers could significantly impact utilization. Expected answer: No changes in coverage or cost. Impact on approach: If confirmed, we'll focus on non-financial barriers to care.
Why it matters: Changes in outreach could affect member awareness and engagement. Expected answer: No significant changes in communication strategies. Impact on approach: If confirmed, we'll need to investigate other factors affecting member engagement.
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