Situation
The client was a leading Healthcare Provider – community hospital affiliated with the large healthcare system. They believed that there were missing claims for healthcare delivered – i.e., charges for legitimate treatments delivered that were never submitted to insurance. The key objective was to identify these missing charges and potentially submit them to recover this revenue.
Approach
- Developed a Machine Learning algorithm to conduct association analysis between diagnostic code for the treatment and the CPT charge code
- Implemented this model across different areas within the hospital such as day surgery, rehab, cardiology etc.
- Identified patient cases where there was a strong association between a diagnostic and CPT code but charges were not filed (e.g., cataract operation and charges for the lens)
- Assimilated these cases across different specialty areas to identify missing charges
- Developed diagnostic and recommendations on reducing these missing charges
Results/Value Created
- Identified more than 500 cases where treatment had been provided but charges were never filed
- Segmented these charges by each specialty area within the hospitals and assessed root causes
- Examined and validated each missing charge to ensure that it was a legitimate charge
- Assisted hospital in filing these charges – leading to increased operating margin by 20%
