INVESTIGATINGHealth & Pharma84% of US health insurers use AI for prior auth. The AI learns which demographics are less likely to appeal and denies them more — a self-reinforcing bias loop. 70% of denials overturned on appeal, proving most were wrong.
“84% of US health insurers use AI for prior auth. The AI learns which demographics are less likely to appeal and denies them more — a self-reinforcing bias loop. 70% of denials overturned on appeal, proving most were wrong.”
84% of American health insurers now use AI for prior authorization — the process that determines whether your insurance will cover a treatment your doctor ordered. The AI doesn't just process claims. It profiles patients. It learns which demographics are less likely to appeal a denial. And it denies those people more often.
The AI tracks appeal rates by demographic. It learns that certain groups — elderly patients, lower-income patients, patients without legal resources — are less likely to fight a denial. So it denies them more frequently. Fewer appeals means more denials stick. More successful denials train the AI to deny even more. It's a self-reinforcing cycle of algorithmic discrimination.
When patients do appeal, 70% of AI-generated denials are overturned. Seven out of ten times, the AI was wrong. The treatment should have been approved. But the insurance companies know most people won't appeal — so the 70% error rate is a feature, not a bug.
Deny everyone. Know that 70% of denials are wrong. Also know that most people won't appeal. The 30% who do appeal get their treatment. The 70% who don't accept the denial and either pay out of pocket, go without care, or die. The AI optimizes for the insurance company's bottom line, not the patient's health.
The elderly. The poor. The uneducated. People without English fluency. People without lawyers. The AI has learned that these groups submit fewer appeals — so it denies them more aggressively. An algorithm is automating discrimination against the most vulnerable people in the healthcare system.
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