Case Study: Stabilizing RAF With Pre-Bill Documentation Validation

Customer profile

A value-based care organization responsible for ~35,000–90,000 Medicare Advantage lives, operating across multiple outpatient sites and affiliated provider groups.

Their population included a large portion of members with complex, chronic needs—where Hierarchical Condition Category (HCC) capture and documentation defensibility directly impacted performance payments and year-end audit exposure.

Teams involved

Cross-functional teams involved included:

• Risk Adjustment Operations (RA Ops) — program lead and analyst support.
• Clinical Documentation Integrity and Coding (CDI/Coding) — centralized team supporting multiple sites.
• Compliance and Audit Readiness — oversight for defensibility and audit preparation.
• Clinical Leadership — medical director and a small group of provider champions.

Why this mattered

By 2026, organizations that win in risk-bearing models aren’t simply “coding more.” They are reducing documentation risk before it becomes financial volatility, shortening cycles between care delivered and performance recognized, operating audit-ready year-round, and protecting margins under tighter scrutiny.

This organization was feeling pressure on all four and they didn’t have budget or appetite for a long implementation cycle.

Challenge

Providers were documenting chronic conditions, but the organization was repeatedly caught in the gap between what was written and what would hold up.

Across internal quality assurance (QA) and chart review cycles, the same problems surfaced:

• Conditions were documented but later invalidated during review because support was incomplete, outdated, or not clearly tied to the relevant encounter.
• HCCs were dropped during reconciliation because the evidence wasn’t obvious at the moment decisions were made.
• Teams faced a last-minute scramble ahead of Risk Adjustment Data Validation (RADV)-style defensibility checks.
• Providers recorded conditions in narrative form without enough current-year assessment and plan language.
• CDI/Coding teams spent time hunting for proof instead of validating it quickly.

The root issue: timing and visibility

The core issue wasn’t lack of effort, it was timing and visibility.

Documentation gaps were being discovered after downstream cycles had already begun, when fixes were slower, more expensive, and more disruptive.

When gaps were found late, the cost compounded:

• Additional provider queries.
• Manual chart chasing.
• Repeated rework.
• Tension between central coding teams and clinic workflows.

What they tried before (and why it didn’t stick)

End-of-year chart sweeps helped catch obvious misses, but they came too late and often couldn’t establish encounter-specific defensibility without significant extra work.

Manual coder queries and spreadsheet workflows were inconsistent across sites, difficult to track, and rarely created accountability or a repeatable feedback loop.

Point solutions that flagged problems highlighted risk, but did not reliably connect each diagnosis to encounter-linked evidence in a way reviewers trusted.

Provider education alone improved awareness, but behavior didn’t change consistently without workflow reinforcement at the point of documentation and review.

Why SynchroLink AI

The organization wanted a workflow that:

• Works before review cycles lock.
• Makes documentation defensibility obvious, not subjective.
• Reduces back and forth with providers.
• Produces evidence packaging that holds up under scrutiny.
• Can be implemented without a multi-quarter project.

Implementation

SynchroLink AI was deployed as a pre-bill documentation validation layer, bridging the gap between “what’s in the chart” and “what the organization is willing to stand behind.”

The rollout was designed to minimize disruption while proving value quickly.

The goal was not to change provider workflow overnight, but to make documentation support clearer and easier to validate before downstream reconciliation and audit preparation.

• Week 1: Define target clinics and prioritize high-impact conditions for review focus.
• Week 2: Configure workflows and bring initial users into a shared review rhythm.
• Weeks 3–4: Operationalize with CDI/Coding and clinical leadership, refine based on real usage.
• Week 5+: Expand coverage once the workflow stabilized.

What changed? From “review everything” to “review what matters”

Before SynchroLink AI, review effort was spread thin. Teams tried to look at as many charts as possible, regardless of impact.

After deployment, the organization adopted a more deliberate rhythm:

• Effort was focused on patients where documentation gaps were most likely to affect risk adjustment results.
• Lower-impact charts stopped consuming disproportionate time.
• Weekly review cycles became predictable instead of reactive.
• This reduced noise and helped teams use limited capacity more effectively.

Teams knew what would hold up before it moved forward

Previously, reviewers often didn’t realize documentation was weak until downstream cycles had already started.

With SynchroLink AI in place:

• Supported and unsupported diagnoses were clearly differentiated.
• Reviewers could quickly see what they could confidently stand behind.
• Leadership had fewer “surprise” discoveries during reconciliation or audit prep.
• Decision-making moved earlier in the process, when fixes were cheaper and faster.

Documentation defensibility became visible, not abstract

“MEAT compliance” had existed as a concept, but it wasn’t consistently operationalized.

We made supporting documentation concrete:

• Reviewers could see whether monitoring, evaluation, assessment, and treatment were actually present.
• Gaps were obvious and actionable instead of subjective.
• Evidence was tied directly to encounters, not scattered across the chart.
• This reduced internal debate and sped up reviews.

Time and recency stopped being hidden failure points

A recurring problem wasn’t missing evidence, it was evidence that was outdated, disconnected from the current year, or difficult to contextualize quickly.

With better visibility across time, teams could distinguish what was still defensible, what needed to be refreshed, and what should not move forward.

This eliminated a common source of audit risk.

Provider outreach became proactive instead of reactive

Before SynchroLink AI, documentation feedback often came late, inconsistently, or without context.

Afterward:

• Documentation gaps were routed back while visits were still recent.
• Providers received clearer, more specific requests.
• Repeated misses decreased because expectations were reinforced in workflow, not just training.
• The organization moved away from passive education toward a repeatable feedback loop.

Audit preparation stopped being a fire drill

When reviews or audits occurred, teams no longer had to reconstruct context from scratch.

Supporting documentation was already organized, encounter-linked, and review ready.

Audit preparation became faster and more predictable, reducing stress and internal friction.

Leadership gained operational visibility without chasing reports

Instead of relying on anecdotes or one off escalations, leadership could see where documentation gaps clustered, what issues were being resolved, and which patterns repeated across sites.

This allowed targeted intervention instead of broad, unfocused initiatives.

Results (60–90 days)

Within the first 60–90 days, teams reported:

• Fewer charts entering downstream review with “surprise” documentation gaps.
• Earlier closure of documentation issues while encounters were still recent.
• Less time spent searching for evidence because it was visible at the decision point.
• Improved confidence heading into audit season due to encounter-linked, organized support.
• Better alignment between centralized CDI/Coding teams and clinics due to clearer ownership and routing.

Why it mattered

This organization wasn’t trying to code more volume. They were trying to reduce volatility and avoid preventable exposure.

SynchroLink AI helped them shift from “discover gaps late and scramble” to “prevent documentation risk before it impacts performance.”

CTA

If you’d like, we’ll run a short pilot and produce a before/after readout focused on:

• Documentation risk reduced.
• Time to close gaps.
• Audit readiness improvements.