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UnitedHealth uses AI model with 90% error rate to deny care, lawsuit alleges | For the largest health insurer in the US, AI’s error rate is like a feature, not a bug::For the largest health insurer in the US, AI’s error rate is like a feature, not a bug.
This is the best summary I could come up with:
The investigation’s findings stem from internal documents and communications the outlet obtained, as well as interviews with former employees of NaviHealth, the UnitedHealth subsidiary that developed the AI algorithm called nH Predict.
The algorithm estimates how much post-acute care a patient on a Medicare Advantage Plan will need after an acute injury, illness, or event, like a fall or a stroke.
It’s unclear how nH Predict works exactly, but it reportedly estimates post-acute care by pulling information from a database containing medical cases from 6 million patients.
NaviHealth case managers plug in certain information about a given patient—including age, living situation, and physical functions—and the AI algorithm spits out estimates based on similar patients in the database.
But Lynch noted to Stat that the algorithm doesn’t account for many relevant factors in a patient’s health and recovery time, including comorbidities and things that occur during stays, like if they develop pneumonia while in the hospital or catch COVID-19 in a nursing home.
Since UnitedHealth acquired NaviHealth in 2020, former employees told Stat that the company’s focus shifted from patient advocacy to performance metrics and keeping post-acute care as short and lean as possible.
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