A repeat pass may improve confidence. It almost always increases the time and cost.
Most risk adjustment programs still run the same records through multi-pass review: another vendor, another queue, another set of eyes, on the theory that more review buys more accuracy. Often it does, at least early on. But the returns shrink with each pass, while the time spent and coordination keep climbing.
That model made sense when tools could flag a diagnosis but not stand behind it. That constraint is gone. When a single pass can be both accurate and defensible, adding more of them buys less than it used to. The smarter move is not another pass. It is a better one.
The Real Cost of Multi-Pass Review
Multi-pass review looks like diligence. In the books, it reads as an expense.
Each additional pass adds more cost and more hours to charts that have already been reviewed. Turnaround slows because a chart is not finished when it is coded. It sits, waiting for the next queue and the next handoff.
Split those passes across vendors, and someone has to manage the seams. Files move back and forth. Guidelines and formats drift between reviewers. Version control becomes its own job. None of that work touches a single diagnosis, yet it drains budget and attention that belong to harder cases.
Multi-pass review also breeds layered disagreement. One reviewer reads a chart one way, another reads it differently, and reconciling the two is another round of manual effort. So teams put their most experienced people on charts that were already settled, while the complex cases wait. As the model scales, cost climbs and turnaround slows.
Why OnePass Defensible Coding Is the New Standard
Even a perfectly coded chart is no longer enough.
Risk adjustment has moved from finding diagnoses to proving them. Defensible risk adjustment coding means every submitted HCC stands on its own: supported by documentation, backed by clinical evidence, and justified for its inclusion. A code without that trail is a liability, however many times it was reviewed.
The pressure behind that shift is not theoretical. CMS is now moving to audit every eligible Medicare Advantage contract each year, not a sample. OIG has stated that failing to remove unsupported codes is a compliance concern, and its recent audits found that most sampled high-risk diagnoses across several plans were not supported by the record. When the test shifts from how many codes you capture to whether each one survives review, more passes no longer suffice.
More review does not close that gap. A chart can pass through multi-pass review and still carry a diagnosis no one can defend, because each pass checks for accuracy rather than building evidence.
Defensibility is not a volume problem. It is a design problem. The question for risk adjustment leaders is not how to review more, but how to make each code audit-ready the first time.
Want the compliance case first?
What RAAPID OnePass Does Differently
RAAPID OnePass is the better pass. It replaces multi-pass review with a single intelligent workflow, powered by neuro-symbolic AI, that produces evidence-backed coding ready to defend, not just ready to submit.
Two-way coding (add and delete)
Defensible coding runs in both directions. It adds diagnoses that a chart supports but earlier reviews missed, and it removes diagnoses the record does not support. Most retrospective programs only do the first half. They add, and they never subtract.
Audit exposure doesn’t come only from add-only reviews. It also comes from unlinked chart reviews, where diagnoses are added without clear clinical evidence or documentation linking them to the submitted code. With the finalized CY2027 Medicare Advantage rule taking effect in about five months, CMS is placing greater emphasis on ensuring submitted diagnoses are supported by acceptable documentation and valid data sources. Exposure can also arise when resolved, historical, or status conditions are reported as active diagnoses without sufficient support. These are exactly the kinds of records that attract scrutiny during CMS and DOJ reviews.
An add-only review is where exposure builds. A program that keeps adding codes but never removes unsupported ones piles up diagnoses it cannot defend, and that one-directional pattern is exactly what OIG and DOJ have flagged.
Two-way coding closes the gap. Removing an unsupported code is not a loss of value. It is a risk you no longer carry into an audit.
MEAT evidence on every code
Evidence is the difference between a code that holds up under audit and one that does not. RAAPID ties every diagnosis to MEAT evidence in the record: proof the condition was Monitored, Evaluated, Assessed, and Treated.
A diagnosis a clinician tracked, worked up, judged, and acted on provides the evidence needed to support defensible coding. Capturing that evidence at the point of coding is what makes a chart audit-ready instead of audit-exposed.
MEAT evidence is an important foundation for defensible coding while also ensuring that acceptable encounter, provider, and CMS-recognized source requirements are met. OnePass validates both the clinical evidence and the source of the diagnosis, helping ensure every submitted code is ready to defend, not just ready to submit.
AI-assisted Coding
OnePass does not remove the coder. It removes the repetition.
The neural layer reads the chart and surfaces diagnoses and evidence the way an experienced reviewer would. The symbolic layer tests each one against coding logic and clinical rules. Then an expert coder validates and makes the call. Final authority stays with the human.
Every code the workflow surfaces carries its own code justification: what supports it, where it sits in the record, and why it qualifies. Reviewers see the reasoning, not just the recommendation, so a chart questioned later already carries its defense.
Audit-ready coding in a single pass sounds ambitious, and skepticism is fair. The numbers back it up. On its own, RAAPID’s AI reached 92% coding accuracy (independent evaluation). Add a single expert review, and accuracy moves past 98% (internal benchmark), with an evidence trail behind every submitted code.
The first plans to move beyond multi-pass review will not just reduce cost. They will define the new benchmark for defensible risk adjustment. The question is no longer how many passes you can afford. It is why you are still paying for them.
Book a demo and see how one evidence-linked pass replaces the rest on your own charts.
Frequently Asked Questions
What is multi-pass risk adjustment coding?
Multi-pass risk adjustment coding is the practice of reviewing the same patient chart multiple times, often across different coders, teams, or vendors, to improve coding accuracy and identify missed diagnoses. While additional passes can increase confidence, they also add time, cost, and operational complexity.
What is OnePass of Defensibility?
OnePass of Defensibility is RAAPID’s approach to risk adjustment coding, combining AI-assisted analysis with expert-coder validation within a single workflow. Every submitted diagnosis is supported by clinical evidence and code justification, helping plans achieve accurate, evidence-backed, and audit-ready coding without relying on repeated review cycles.
How does AI improve risk adjustment coding?
AI helps risk adjustment coding by analyzing clinical documentation, identifying potential diagnoses, surfacing supporting evidence, and reducing manual chart review time. When combined with expert coders, AI improves coding efficiency while helping to ensure that every diagnosis is supported by the documentation needed for audit readiness.
Why is MEAT documentation important in risk adjustment?
MEAT documentation demonstrates that a condition was Monitored, Evaluated, Assessed, or Treated during the encounter. It provides the clinical evidence needed to support HCC diagnoses, making submitted codes more defensible during RADV and other compliance audits.
What is RADV audit readiness?
RADV audit readiness refers to a health plan’s ability to defend submitted diagnosis codes with complete documentation and evidence during CMS audit reviews.
Read more: RADV Audit Checklist
References
[1] OIG Medicare Advantage compliance audit, A-07-22-01207
[2] OIG Medicare Advantage compliance audit, A-07-22-01208
[3] OIG Medicare Advantage compliance audit, A-03-22-00004
[4] OIG Medicare Advantage Compliance Program Guidance (Feb 2026)
[5] DOJ Aetna/CVS settlement ($117.7M)
