Subrogation

Recovery Identification

Data-Driven Approach

Identifying cases and achieving recoveries with transparency.

When another party is responsible for a member’s injury or illness, missed subrogation opportunities can quietly drive up costs.

Claritev’s Subrogation solution uses advanced analytics, machine learning, and experienced specialists to identify claims you’re not responsible for paying and focus efforts on the cases most likely to result in recovery.

Higher Recoveries

Fewer Low-Value Investigations

Efficient Member-Friendly Experiences

Full Transparency from Start to Finish

Data-driven
transparency
across the entire
subrogation process.

Automated Case Identification


Claritev focuses on the subrogation cases most likely to deliver recoveries. Using automation and machine learning, we analyze your data to identify and score high-potential cases, so we know where to prioritize your efforts.

You can guide the analysis with your own parameters, create cases manually if needed, and automatically import claims without heavy data entry.


Through this process, we eliminate

35%


of cases that won’t likely result in a recovery.

End-to-End Subrogation Support

Create workflows with our diary system

Store group health plan language

Manage and configure letter templates with the fields you need so you can determine which letters are used with each case

Scan incoming letters into your cases

Configure closing codes, lifecycle codes, diaries, and prewritten notes

View an audit trail that includes date, time, and user stamps for each activity performed at the case level

See all claims in a case according to configurable views

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Pattern

Learn how Claritev can help maximize recoveries and prevent overpayments with data-driven solutions.