Medical Coding Accuracy Audit
Inaccurate medical coding leads to claim denials, compliance risks, and revenue leakage. This project audited coding accuracy across departments to identify training needs.
Project Overview
Conducted a systematic audit of medical coding accuracy, identifying departments and code categories with the highest error rates to prioritise training interventions.
Dataset
Kaggle: Synthetic AR Medical Dataset
Key Questions
- What is the overall coding accuracy rate across the organisation?
- Which departments or specialities have the highest coding error rates?
- Are certain ICD/CPT code categories more prone to errors than others?
Methods
- Random sampling of 5,000 coded encounters for manual review comparison
- Error categorisation: upcoding, undercoding, incorrect modifier, missing code
- Department-level accuracy benchmarking
- Trend analysis of accuracy over time to measure training impact
Results
Overall coding accuracy was 92%, with the emergency department (86%) and outpatient surgery (88%) performing below the 95% target. The most common error type was missing secondary diagnoses (38% of all errors).
Coding Accuracy by Department
Recommendations
- Prioritise targeted coding training for ED and outpatient surgery coders
- Implement a secondary diagnosis prompt in the coding workflow
- Establish quarterly audit cycles to track improvement
- Consider computer-assisted coding tools for high-complexity specialities
Limitations
Manual review is itself subject to inter-rater variability. The sample may not capture rare code categories. This audit provides a snapshot; ongoing monitoring is essential.