Developer Reframes Prior Authorization as a Data-Matching Problem to Cut Denials

A software developer spent a year building tools to address the chronic inefficiency of medical prior authorizations, concluding the core challenge is not generating persuasive text but systematically matching each payer policy criterion to specific, dated evidence in a patient's chart. Rather than relying on AI to draft medical necessity letters, the approach maps every required criterion to a traceable chart citation, flagging unmet criteria as denial risks before submission. Different insurers such as Aetna and UnitedHealthcare require distinct sets of criteria for the same procedure, making payer-specific policy parsing essential. The system treats any evidence that cannot be traced to a real chart entry as unsatisfied, since a fabricated citation poses greater risk than a flagged gap. When denials do occur, the same criterion-to-evidence framework is applied in reverse to build targeted, point-by-point appeals using the payer's own policy language.