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Claims Denial Rate Analysis
High claims denial rates reduce revenue and create administrative burden. This project investigated which claim types and payers had the highest denial rates and why.
Reduced denials by 18% in simulation
2025PythonSQLPandasPower BI
Dataset
Kaggle: Synthetic AR Medical Dataset
Key Questions
- Which payers and procedure categories have the highest denial rates?
- Are there patterns in the timing of claim submissions that correlate with denials?
- What are the most common denial reason codes, and are any preventable?
Methods
- SQL-based extraction and aggregation of claims by payer, procedure, and month
- Pareto analysis of denial reason codes
- Chi-square tests for independence between payer type and denial outcome
- Dashboard development with drill-down by department and payer
Results
Three payers accounted for 60% of all denials. The top denial reason was 'missing documentation' (32%), followed by 'coding errors' (24%). Claims submitted on Fridays had 15% higher denial rates than mid-week submissions.
Denial Rate Distribution by Reason
Recommendations
- Implement a pre-submission checklist for the three highest-denial payers
- Automate documentation completeness checks before claim submission
- Shift claim submission deadlines away from Fridays to reduce error rates
- Provide targeted coding training for the top 5 most-denied procedure categories
Limitations
This analysis uses a synthetic dataset, so the specific denial patterns may not reflect real-world payer behaviour. The simulation of an 18% reduction is based on eliminating preventable errors and would need validation in practice.