The original title is "Modeling Prior Authorization as a Payer-Policy Matching Problem"

Short summary

Prior authorization denials happen because criteria-to-evidence binding fails. Instead of using AI to generate persuasive letters, model prior auth as a matching problem: enumerate payer criteria, bind each to chart evidence, flag gaps before submission. Appeals work by rebutting denial reasons point-by-point with targeted evidence.

• •Prior auth isn't document generation—it's criteria-to-evidence matching
• •Build systems that expose unmet criteria before submission to reduce denial risk
• •Appeals work by rebutting each denial reason with targeted evidence from your matching bindings

Generated with AI, which can make mistakes.