OrchestriAI
HealthcareAI AgentsRegional medical billing department, 5-person team

Tripling Claim Denial Recovery with a Multi-Agent System

Appealable denial recovery rate went from 40% to 71%. The team now handles 3x the claim volume with the same headcount.

Verified client engagementBy Shariq Riaz ·

Engagement map

From operating problem to measured outcome

8 weeks delivery · 4 tools in the implementation stack

  1. 01
    01Regional medical billing department, 5-person team

    Challenge

    A 5-person medical billing team was manually triaging every claim denial.

  2. 02
    02AI agents + eClinicalWorks

    What we built

    We built a 4-agent pipeline: an intake agent classifies denial reason codes and identifies appeal viability based on payer history, a research agent pulls relevant clinical documentation from the EHR, a drafting agent writes the appeal letter in the payer's required format, and a compliance agent reviews the draft against payer-specific guidelines.

  3. 03
    038 weeks

    Result

    Recovery rate on appealable denials improved from ~40% to 71%.

Recorded outcomes

Denial recovery rate
40% → 71%Engagement result
Claims volume handled
3× increaseEngagement result
Misclassified denials caught
22%Engagement result

Delivery timeline: 8 weeks. Metrics are shown in the same context as the published engagement.

Source providedVerified client engagement

Problem, implementation, outcome

01

Challenge

A 5-person medical billing team was manually triaging every claim denial. Open the denial, read the reason code, decide if it was worth appealing, gather supporting documentation, write the appeal letter, submit it. For a team processing 250+ claims a month with a 15–18% denial rate, that was 40–50 denials to handle manually every month, each taking 20–45 minutes depending on complexity. Some viable appeals were being written off simply because the team didn't have capacity.

02

What we built

We built a 4-agent pipeline: an intake agent classifies denial reason codes and identifies appeal viability based on payer history, a research agent pulls relevant clinical documentation from the EHR, a drafting agent writes the appeal letter in the payer's required format, and a compliance agent reviews the draft against payer-specific guidelines. Staff receives a complete, reviewed appeal package. They read, approve or edit, and submit. The system doesn't submit without human sign-off.

03

Result

Recovery rate on appealable denials improved from ~40% to 71%. The team took on billing for two additional practices without adding headcount. The less obvious win: the intake agent was catching denial reasons previously misclassified as non-appealable. About 22% of what staff had been marking 'not worth appealing' was actually viable, mostly clinical necessity denials with documentation that supported the appeal.

Implementation stack

AI agents
eClinicalWorks
Custom APIs
Document processors
Delivery timeline: 8 weeks

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