Prior authorization in minutes: document AI for the healthcare back office

The problem

At a multi-site provider group, prior authorization was a full-time paper chase. Staff cross-referenced each request against payer-specific requirements — which vary by plan and change quietly — then hunted through records for the supporting documentation. Packets took hours each; missing documents drove denials; denials drove rework and delayed care.

The hypothesis

Prior auth is a matching problem: what the payer requires versus what the record contains. Our hypothesis: encode payer requirements as structured checklists, use document AI to locate the evidence in the record, and let the system assemble the packet — with humans confirming anything ambiguous and signing every submission.

The build

• Requirements library — payer rules captured as versioned, structured checklists, maintained as plans update.
• Document AI extraction — models locate and extract the relevant clinical evidence — notes, labs, imaging reports — and map each item to the checklist.
• Packet assembly + gap flags — the system compiles the submission, marks anything missing or low-confidence, and routes gaps to staff before anything goes out. Every packet carries a full evidence trail.

Rollout

We started with the three highest-volume procedure families and two payers, ran assembled packets against staff-built ones for agreement, and expanded coverage payer by payer as the requirements library matured. PHI handling was designed with the compliance team from day zero — least-privilege access, audit logging, no data used for model training.

Results

Packet assembly dropped from hours to minutes for covered procedures. Denials tied to missing documentation fell, staff shifted from hunting documents to reviewing flagged gaps, and — critically for a regulated environment — every submission is now reconstructable end to end.

What we'd tell you

• The requirements library is half the system. Treat payer rules as versioned data, not tribal knowledge.
• Route uncertainty to people. In clinical contexts, "flag it" always beats "guess well."
• Bring compliance in at the architecture stage — retrofitting PHI controls is where these projects die.