07: Paying for Care
How we pay for care delivered to our members.
4 AI use cases
Configure Claims
Configure our payments systems quickly, reliably, dynamically and while minimizing errors.
Set Up Network Contracts
Configure the rules for how we pay for care, and enable payment terms that incentivize providers to deliver the best possible care and outcomes
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Status: Pilot / Prototype
One of the key inputs into the processing of a health insurance claim is the contractual language that was agreed on between payor and provider. These agreements are often non-standardized, and even small discrepancies in how they’re configured can delay payment and cause headaches for patients. With AI, we’re exploring ways to automate the translation of provider contracts into highly accurate claims configurations.
Set Up Benefits, Plans, Logic
Configure the rules for which kind of care we pay, and enable complex product designs that drive affordability for members, and which other insurers are unable to copy
Pay Claims
Adjudicate and pay claims to providers with highest automation, fastest speed and no friction
Reward High-value Provider Behavior
Pay providers for value, for outcomes, and for working with us in an integrated way, and not just for fee-for-service.
Adjudicate & Adjust Claims
Pay the fastest, with no errors, and in the most self-explanatory way possible.
Receive Claims
Know as quickly as possible when care was delivered, so we have a real-time pulse on what’s going on.
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Status: Idea / Exploration
Just like paper prior auths, manually submitted paper claims remain part of the reality of health insurance. However, AI offers a path to streamlining the processing of these claims by extracting claim attributes from free form documents either by chaining together OCR and LLM-based text parsing or through a multi-modal LLM.
Run Payments Surveillance
Don’t pay for anything that doesn’t help members.
Reduce Fraud, Waste & Abuse
In a highly automated way, reduce overpayments for inappropriate utilization.
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Status: Pilot / Prototype
Health plans spend a lot of energy maintaining up-to-date information on the providers in their network. At Oscar, we do this in a variety of ways and get signals from a variety of sources. We’ve prototyped automating intake for parts of this pipeline to streamline the processing of externally reported or internally identified provider data issues.