Reducing health insurance costs and improving care

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Summary

Oscar Health has successfully deployed OpenAI's API to automate clinical documentation and claims processing, reducing documentation time by 40% and claims resolution time by 50%, while establishing an AI Pod to guide responsible AI adoption across the organization.

Oscar brings AI to health insurance, reducing costs and improving patient care.
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# Reducing health insurance costs and improving care Source: [https://openai.com/index/oscar/](https://openai.com/index/oscar/) Oscar has used AI to speed up and automate tedious manual processes that drive up healthcare costs\. They found success with the following use cases: **Clinical documentation\.**Documenting a single conversation between a patient and the medical team can take a human more than 20 minutes\. With OpenAI’s API, Oscar has cut the time spent documenting medical care conversations and reviewing lab test results by nearly 40%, saving countless hours across the company and less tangibly, reducing burnout by allowing nurses and clinicians to focus on higher\-order tasks\. This is just the beginning—R&D shows that GPT‑4 can get productivity gains up to 90% in some cases\. **Building a claims assistant\.**Understanding the life story of a claim is incredibly complex work, as there are millions of contractual variables at play\. When a doctor has a question about a claim, Oscar’s teams must navigate detailed logs of every decision made throughout a claim’s processing journey\. With OpenAI’s API, Oscar has built an assistant that navigates the claim trace efficiently and automates the process of answering questions about the patient’s claims\. The claims assistant has reduced the time it takes for the claims processing team to resolve escalations by 50%, with accuracy on par or better than human agents\. Oscar expects to automate investigation for at least 4,000 tickets per month, or 48,000 tickets by the end of the year\. Oscar hasn’t just embraced AI—they live and breathe it\. The company has set up a centralized AI Pod whose mandate is to shepherd other teams like product, data science, and operations through the process of applying AI to their use cases\. Rather than using AI for AI’s sake, Oscar believes that fully understanding the business problems upfront is the key to success\. “We’ve seen that the most successful applications happen when we’re able to break down a very complicated problem into bite\-sized tasks,” Luthra explained\. This guides the talent philosophy, with Oscar focusing on grit, humility, and curiosity over publication citations or academic accolades: “The people who can do that are the ones who are extremely curious about how humans break down problems in the real world\. Five of the six people in our Pod are women, and all of us are in our twenties and thirties—which shows that there’s not one stereotype of who is pushing the frontiers of AI development\.” Oscar has also self\-regulated, proactively setting standards to ensure that AI is used responsibly and ethically in healthcare\. In partnership with the White House, they’ve led a coalition of 37 of the biggest healthcare payers and providers to collectively develop and adhere to[principles for AI use⁠\(opens in a new window\)](https://www.healthcareaicommitments.com/)\. Oscar proudly shares generative AI insights on their company blog and social media\. “People are all grappling with the same issues in healthcare,” Schlosser said\. “If we solve a problem first, we should tell others about it—they’ll tell us what they solved, too, and that’s a fantastic way of getting the flywheel spinning\.”From the beginning, Oscar has viewed AI as more than just a tool for automating rote tasks—they see it as the key to unlocking a much\-needed revolution in healthcare\. “We don’t just want to nibble around the edges of administrative use case simplification,” Schlosser said\. “We should aspire to use these models to help solve a clinical issue with your doctor\. In the next three to five years, we need to bring down the cost of seeing physicians and being in the hospital by a factor of 10\. The only way to do that is to have a model front\-and\-center—not just scribing, but integrating into member\-provider interactions\.”

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