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    Machine Learning Drives Efficiencies at Claritev

    Machine learning is helping drive efficiency and accuracy across healthcare operations by enabling systems to learn from data and automate complex processes. At Claritev, this technology is used to prioritize claim reviews and enhance payment integrity, allowing teams to focus on high-value tasks, reduce manual effort, and scale operations while delivering greater value to clients.

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    Case Study: Retaining important business

    Claritev analysis helped a third-party administrator defend against a competitor’s push to implement Medicare pricing by: significantly improving savings for the employer and its members; engaging important providers in the new process; and preserving the community’s provider-patient relationships.

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    Case Study: Navigating a challenging environment

    An auto medical services provider wanted to distinguish its network-based cost management program to sensitive auto insurance carriers by demonstrating: minimal provider noise through the use of network contracts to reduce medical cost; effective dispute resolution processing.

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    Case Study: Meeting a specific need quickly

    A health plan facing tight deadlines needed rapid access to providers to meet network adequacy requirements. By leveraging existing contracted providers and targeted credentialing strategies, Claritev enabled faster network expansion—helping the plan meet compliance requirements, accelerate market entry, and maintain flexibility for future growth.

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    Case Study: Fixing vs. paying improper charges

    Claritev analysis uncovered opportunities for a third-party administrator using a variety of PPO networks to: improve payment accuracy – too much was being missed in the existing editing process; gain control over clinical billing waste and abuse; and minimize provider abrasion to preserve leased network relationships.

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    Case Study: Partnering to achieve certification

    A workers’ comp services provider needed help maintaining State Certified Managed Care programs by: eliminating provider coverage gaps in geographies not addressed by its proprietary network; strengthening coverage for key medical specialties.

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    Case Study: Leveling the playing field

    To improve competitiveness, a regional provider-owned health plan needed assistance with: extending network access for its highly mobile membership, containing out-of-network medical cost, and preserving its relationships and reputation with the local provider community.

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    Case Study: Extending the Power of Bill Review

    Claritev analysis showed a property and casualty servicer how it could strengthen its bill review and network services by: using analytics tuned to find wasteful or abusive medical billing practices not identifiable by more automated bill review programs; implementing resolution strategies appropriate for the severity of issues and nature of the provider relationships.