CASE STUDY
10-hospital system recovers $5M missed by existing vendors.
Ensemble uses AI to detect and prevent potential underpayments.
SNAPSHOT
Despite working with multiple underpayment vendors, a southeastern health system felt it was missing out on revenue opportunities and wanted a more tactical, hands-on approach. It engaged Ensemble to perform a deep dive into its accounts to recover revenue and prevent future underpayments.
Ensemble deployed AI to eliminate false variances and detected anomalies missed by others and applied best practices to recover $5 million and prevent $1.5 million in underpayments annually.
PROFILE
- Academic health system, 10+ hospitals
- $1B+ NPR
- Southeast
- Underpayments recovery tertiary partner
Challenges
A detailed review of the health system’s accounts revealed that zero-balance accounts and contracts were not fully leveraged for revenue recovery opportunities. Furthermore, recurring errors and process failures were identified.
Solutions
By applying best practices and RCM intelligence powered by AI to sift through data, our experts uncovered recovery opportunities, contractual issues and areas for process improvement to prevent future losses.
- Identifying + improving front-end processes that would prevent future underpayment
- Utilizing AI-driven automation to thoroughly review all accounts, eliminate false variances and detect anomalies that had gone unnoticed by other vendors
- Recognizing significant contractual issues to leverage during payer contract negotiations
Results
over 4 years
inpatient blood transfusions