Auto-Adjudication

One health plan ran a 0% auto-adjudication rate on a 30-year-old legacy claims system. After modernizing to a current platform, that same plan exceeded 90%, according to a HealthEdge case study on McLaren Health Plan. That gap represents millions of dollars in operational cost and thousands of hours in processing time — and it illustrates exactly why auto-adjudication deserves your attention.

What Is Auto-Adjudication?

Auto-adjudication is how your claims processing system evaluates an incoming claim against defined rules — benefit coverage, eligibility status, coding validity, and contracted rates — then automatically approves or denies it without a claims examiner ever touching it. When the system can confidently resolve every required check on its own, the claim qualifies for auto-adjudication.

Claims with ambiguous coding, missing information, coordination of benefits (COB) questions, or characteristics the rules engine can't confidently interpret get routed to manual review instead.

Your auto-adjudication rate depends on the combined effect of data quality, rules engine sophistication, and how standardized your benefit structures are. Non-standard benefit designs inherently generate more claims a generic rules engine can't confidently resolve. And because manually reviewed claims cost much more and take longer to process, your auto-adjudication rate functions as a core measure of operational health.

Why Your Auto-Adjudication Rate Directly Hits Your Bottom Line

The cost differential between automated and manual claims processing is large enough that even modest shifts produce meaningful financial impact at typical claim volumes. Consider what a five-percentage-point improvement means when you're processing millions of claims annually — each manually reviewed claim carrying multiples of the cost.

Higher auto-adjudication rates also tend to reduce payment errors and resulting appeals. A well-configured rules engine applies identical logic to every claim. Manual review, performed by different examiners under time pressure, introduces inconsistency.

Here's what catches many plans off guard: your auto-adjudication rate can decline even without any change in claims volume. Evolving regulations and payment guidance can force previously auto-adjudicated claim types into manual queues while you update system configurations to align with new rules.  If you're not actively monitoring rate trends, a regulatory shift can quietly erode your operational efficiency before anyone flags it.

How Auto-Adjudication Works

The process moves a claim from intake through automatic determination, with exceptions routed to human review:

• Claim intake: A submitted claim enters your claims processing system, typically through an Electronic Data Interchange (EDI) feed.
• Rules evaluation: The claim is checked against eligibility, benefit coverage, coding validity, contracted rates, and other defined business rules.
• Automatic determination: If every check resolves confidently, the system automatically approves or denies the claim without human involvement.
• Manual routing for exceptions: Claims the rules engine can't confidently resolve — ambiguous coding, missing data, COB questions — are routed to a human examiner.
• Rule refinement: Recurring reasons claims fall into manual review are analyzed to determine whether the rules engine, data source, or upstream process can be improved to raise future auto-adjudication rates.

That last step is where the real payoff sits. Every pattern you identify and address in your rules engine compounds over time, steadily shifting claims out of expensive manual queues.

Key Metrics and Benchmarks

Health plans generally target an auto-adjudication rate above 80% to 85% as a strong performance benchmark. Industry sources report actual first-pass rates ranging from 10% to 70%, depending heavily on plan complexity, benefit design standardization, and document quality at claim submission.

Plans with non-standard benefit structures or unusual processes tend to run below the industry average. A variance of up to roughly 10 percentage points below average generally reflects plan complexity rather than a poorly performing claims system.

The actionable metric isn't just your current rate — it's the trend. A declining rate, even without a corresponding increase in claim volume, typically signals either a data quality problem creeping into submissions or an unaddressed regulatory change forcing more claims into manual review. Catching that signal early gives you time to act before costs compound.

Your Next Step

Start by benchmarking your current auto-adjudication rate against your plan's complexity profile, not just industry averages. Then identify the top three to five reasons claims are falling out of auto-adjudication into manual review. Those recurring exception categories are your highest-return improvement targets — each one you resolve shifts volume from your most expensive processing path to your least expensive one.

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