The SNIP 6-7 Problem

Much of the healthcare EDI industry runs on a reactive workflow: submit claims, get rejected, manually create an edit, repeat.

That's not just a technology problem - it's how the ecosystem has evolved. Payers release companion guides. Everyone downstream must implement them. And when a new rejection pattern emerges, someone has to manually figure out the rule and add it to the validation system.

Having built validation systems across the claim lifecycle, I've lived this pattern for years.

Here's how payer validation typically works today:

Payer communicates requirements - companion guides, provider portal bulletins, email blasts, sometimes all three with slightly different wording.
Clearinghouses and billing systems try to implement key rules they happen to catch.
Claims get submitted.
Some get rejected for rules nobody caught.
Someone investigates the rejection, figures out the pattern.
They manually create an edit in their system.
Future claims avoid that specific error.
Repeat for the next rejection pattern.

This is SNIP levels 6 and 7. SNIP - Strategic National Implementation Process - defines 7 levels of validation that EDI claims pass through. Levels 1-5 validate against defined standards and external code sets. Levels 6 and 7 are different - service type requirements and payer-specific rules, scattered across hundreds of payer documents, inconsistently formatted, frequently updated, and often discovered only through rejections.

The manual effort feels wasted. Every clearinghouse, every billing vendor, every health system with in-house EDI - they're all doing the same work independently. Monitoring the same portals. Sifting through the same email blasts. Reading the same companion guides. Creating the same edits. Reacting to the same rejections.

In my last few posts, I showed how I'm using AI to extract payer edits into structured rules - the pipeline architecture, how it decomposes the problem, and the honest limitations. But the question I keep coming back to is: why is this manual work happening at all? The goal isn't just automating PDF extraction - it's flipping the model from reactive to proactive.

Instead of: rejection → investigation → manual edit
The goal is: companion guide update → AI extraction → validation rules

But that requires somewhere for the AI to put its output. You need a structured format that's:

Machine-writable: AI can generate it programmatically.
Human-readable: Engineers can review and verify.
Parseable: Can be translated into whatever rule engine you use.

The structured format is half of the innovation. The workflow change completes it.

Today:

Submit claims
Receive 277/835 rejection
Manually create edit in system
Edit scrubs future claims

Goal:

Payer docs → AI extraction → Structured rules
Human review
Validation catches errors before submission

The traditional workflow is entirely reactive. You don't know a rule exists until a claim fails. Then someone logs into their system, manually creates an edit to catch that pattern, and hopes future claims don't hit the same rejection.

The structured format enables a proactive approach. Instead of waiting for rejections, AI reads companion guides, emails, or portal bulletins and extracts rules before you submit claims.

AI-generated rules don't solve SNIP 6-7 complexity. They create a path to address it proactively rather than reactively.