Introduction
The unexpected 30% increase in false positive alerts from Inovalon's INDICES fraud detection system in the last quarter is a critical issue that demands immediate attention. This surge in false positives not only impacts operational efficiency but also risks eroding trust in the system among healthcare providers and payers. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term strategic solutions.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: System changes often lead to unexpected behaviors in complex fraud detection systems. Expected answer: Yes, there was a major update to incorporate new data sources. Impact on approach: If confirmed, we'd focus on validating the new data sources and their integration.
Why it matters: Poor data quality can significantly impact fraud detection accuracy. Expected answer: Some partners have reported issues with their data submission processes. Impact on approach: We'd prioritize data quality audits and partner communication.
Why it matters: Regulatory changes can alter the landscape of what constitutes fraudulent behavior. Expected answer: No major regulatory changes in the past quarter. Impact on approach: We'd shift focus from external factors to internal system dynamics.
Why it matters: Increased load can strain system resources and impact performance. Expected answer: Yes, we've seen a 20% increase in processed claims. Impact on approach: We'd investigate scalability issues and potential resource constraints.
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