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ElectrifAi partnered with one of the nation’s largest health systems with $4B+ in net revenues to streamline the charge reconciliation process and identify potential areas of opportunity.
The health system processed millions of claims annually. The existing rules-based system was insufficient and resource intensive resulting in low findings, high false positives, and high resource cost. As a result, the health system was missing millions of dollars in net revenue due to missed charges and coding errors.
ElectrifAi worked with health system’s revenue integrity team to implement the RevCaptureAi solution to:
- Apply predictive analytics and machine learning algorithms to learn from complex charging patterns and identify missed-charges at account level for both hospital and professional charges
- Integrate with variety of EMR systems in different regions (fully automated process)
- Leverage feedback models to learn from auditors’ responses and make predictions “smarter”
Health System Size
- $10M+ in annual net revenue uplift
- 100% of outpatient accounts analyzed through automated pre-bill and post-bill process
- Identified top departments and areas with systemic gaps in charge capture e.g. Injection/Infusions, EKG, surgery, implants & medical devices