Sample Power BI dashboard demonstrating healthcare risk adjustment analytics and coding trend visualization using synthetic data.
Key Findings
- Acute Stroke and Breast Cancer showed 100% error rate in the reviewed sample
- Overall 84% of high-risk HCC codes were unsupported (252 out of 300 cases)
- Estimated potential overpayment in the reviewed sample: $4.4 Million
- Major compliance risks identified in documentation and coding accuracy
Recommendations
- Strengthen documentation requirements for high-risk conditions (especially Acute Stroke and Cancer)
- Implement regular internal coding audits for high-error HCC categories
- Provide targeted training for coders and providers on proper documentation
- Establish better validation processes before submitting claims to reduce RADV risk
Skills Demonstrated
- Strong domain knowledge in HCC coding and RADV process
- Audit data analysis and risk assessment
- Financial impact modeling
- Compliance and reimbursement risk visualization
Tools Used: Power BI Desktop, DAX, Excel