Since 2021, the Office of Inspector General has employed a new audit methodology to surface non-compliant diagnosis codes, by scrutinizing particular fact patterns in coding data that correlate with improper documentation. It refers to these fact patterns as “Selected High-Risk Diagnosis Codes”. Since integrity in all diagnosis submissions is paramount for Medicare Advantage risk adjustment, health plans are well served by applying OIG’s methodology to their own data, in order to surface and correct these common coding errors, and ultimately better coordinate care. Facility with this type of analysis also empowers a health plan to anticipate other fact patterns in its submissions that may point to improper coding.

Key Takeaways

• Discuss the recent literature from the Office of Inspector General focused on integrity in diagnosis code submissions, and impacts on coding in Medicare Advantage
• Learn the power of data analysis of medical and pharmacy claims for surfacing problematic diagnoses, and of NLP for evaluating these diagnoses
• Understand how to efficiently follow up on high-risk diagnosis codes in preparation for a potential future audit
• Learn what data is available in standard claims is key for customizing and expanding the search for high-risk diagnosis codes

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