CASE STUDY
AI-Powered Claims Review Automation in Healthcare
An intelligent pre-submission Claims AI Review Agent combining LangChain, Ollama, and n8n to reduce claim rejection rates from 15% to 3% and accelerate cash flow by $3.5M annually for a 200+ physician provider group.
Cognic ClaimsAI
Search claim batches or ICD-10 codes…
Pre-Submission Claims Scrubbing & Code Validation
25,000
Monthly Claims Processed
3.1%
Payer Rejection Rate
<12 Hrs
Review Turnaround
$3.5M
Annual Cash Acceleration
| Claim ID | Payer | CPT / ICD-10 Code | Billed Amount | Status / Finding | Confidence |
|---|---|---|---|---|---|
| CLM-77041 | Blue Cross Blue Shield | 99214 / I10, E11.9 | $1,450.00 | Clean Claim – Passed | 99% |
| CLM-77045 | UnitedHealthcare | 73721 / M25.561 | $2,890.00 | Prior Auth Attached | 97% |
| CLM-77049 | Aetna Commercial | 99285 / R07.9 | $3,400.00 | Missing Modifier – Corrected | 95% |
| CLM-77052 | Medicare Part B | 45378 / Z12.11 | $1,120.00 | Preventive Screening Validated | 100% |
| CLM-77058 | Cigna Health | 99204 / M54.5 | $890.00 | Documentation Mismatch | 88% |
25,000 Monthly Claims Scrubbed
Automated code validation across 200+ healthcare providers
< 12 Hours Turnaround Time
Reduced submission review cycle from 5 days to under 12 hours
$3.5M Cash Flow Acceleration
Drastic reduction in denied claims, appeals, and reimbursement lag
80% Less Denials Payer Denial Reduction
Denial rate dropped from 15% to 3.1% in first 90 days
What is AI-powered claims review?
AI-powered claims review is an automated medical billing intelligence engine that analyzes patient clinical records, CPT/HCPCS codes, ICD-10 diagnostic entries, and payer-specific medical necessity rules before electronic submission to insurance clearinghouses.
A Smarter Way to Prevent Healthcare Denials
The Challenge
25,000 monthly claims reviewed manually, creating 5-day submission backlogs and a costly 15% payer rejection rate.
The Solution
Automated pre-submission claims scrubbing engine combining local LLMs (Ollama), LangChain, and EHR data connectors.
The Outcome
Payer denial rate plunged to 3.1%, cash flow accelerated by $3.5M annually, and billing teams eliminated manual code cross-referencing.
The Challenge
Medical provider networks lose millions annually when billing teams miss mismatched modifiers, unbundling errors, or missing clinical documentation.
Over 25,000 monthly insurance claims processed manually by billing staff
12% to 15% claim denial rates caused by coding inconsistencies and missing documentation
Average 5-day review delays between patient discharge and electronic billing
Complex payer-specific rules across Medicare, Medicaid, and commercial plans
Clinical Audit & Compliance (CAC) backlogs threatening regulatory penalties
Billing team fatigue leading to repetitive unbundling and modifier errors
Lengthy appeal cycles tying up millions in uncollected accounts receivable
Lack of real-time root cause analytics to train medical coders
Traditional Manual Billing vs. Cognic Claims AI Scrubbing
| Workflow Stage | Traditional Manual Workflow | Cognic AI-Powered Engine |
|---|---|---|
| Claim Ingestion | Manual export and spreadsheet queue sorting from EHR | Automated EHR webhook intake and structured claim packet parsing |
| Code Cross-Validation | Human coders manually cross-checking ICD-10 & CPT against PDF doctor notes | Semantic LLM analysis validating medical necessity and code coherence in seconds |
| Payer Rule Check | Static paper cheat-sheets often outdated by new policy changes | Dynamic rule engine continuously updated for Medicare, Medicaid, & commercial payers |
| Modifier & Unbundling | High human error rate on complex CCI edits | Automated CCI edit validation preventing unbundling and missing modifier denials |
| Exception Handling | Claims routed through email threads with slow turnaround | Interactive Billing Workbench with highlighted discrepancies and auto-suggested fixes |
| Submission Velocity | 5-7 business days from encounter to clearinghouse dispatch | < 12 hours straight-through submission with 97% first-pass clean rate |
The Cognic Claims Intelligence Engine
Three integrated modules transforming raw clinical encounters into clean, defensible payer claims.
01
Clinical Document & EHR Parser
Extracts operative reports, SOAP notes, lab results, and patient encounter documentation directly from EHRs.
• EHR FHIR & HL7 connectors
• OCR for scanned records
• Medical terminology parsing
→
02
Local LLM & Coding Validator
Cross-checks diagnostic ICD-10 codes against procedural CPT codes using private local LLMs without external data leakage.
• Medical necessity validation
• CCI edit & modifier checks
• Payer policy rule enforcement
→
03
Clearinghouse Dispatcher & Workbench
Automates straight-through 837 EDI submission while routing flagged exceptions to certified medical coders.
• 1-click coder exception approvals
• 837 EDI auto-dispatch
• Denial analytics root-cause tracking
→
Pre-Submission Scrub
Prevents 80%+ of avoidable coding denials
837 EDI Sync
Direct clearinghouse electronic submission
Audit Defensibility
Evidence citation link to chart notes
Claims Processing Pipeline & Architecture
An automated, high-throughput revenue cycle scrubbing architecture.
1 Encounter Ingestion
› FHIR EHR Connector
› SOAP Notes Ingestion
› Operative Reports OCR
› Patient Demographics
› Charge Capture Logs
2 AI Code Scrubbing
› Ollama Local LLM
› ICD-10 / CPT Coherence
› Medical Necessity Check
› CCI Bundling Validator
› Modifier Precision Check
3 Coder Workbench
› Exception Highlighting
› 1-Click Fix Suggestions
› Prior Auth Verification
› Audit Evidence Link
› Coder Sign-Off
4 837 EDI Dispatch
› 837 EDI File Generation
› Clearinghouse API Post
› 277CA Status Tracking
› Payer Remit Sync
› Revenue Analytics
From Clinical Chart to Paid Claim
An end-to-end traceable workflow from doctor encounter to insurance reimbursement.
Patient Chart
→
EHR Intake
→
AI Scrubbing
→
Coder Check
→
837 EDI Post
→
Paid Claim
Claims Intelligence & Scrubbing Layer
Specialized AI capabilities powering pre-submission claim validation.
Medical Necessity Verification
Validates that procedural CPT codes match clinical indications in doctor notes
CCI Bundling & Modifier Engine
Detects unbundled services and auto-suggests correct modifiers (e.g., 25, 59)
Local LLM Zero PHI Exposure
Runs fully inside private VPC on local Ollama Llama 3 models without cloud leakage
Payer-Specific Policy Rules
Dynamic validation against Medicare NCD/LCD and commercial insurance guidelines
Automated 837 EDI Formatting
Packages clean claims into HIPAA-compliant EDI transactions for instant dispatch
Certified Coder Review & Scrubbing Workbench
Medical coders and billing managers review flagged claims with highlighted discrepancies and auto-suggested coding adjustments.
| Claim ID | Payer & Patient | Discrepancy / Rule Flag | AI Recommendation | Action | ||
|---|---|---|---|---|---|---|
| CLM-99214 | BCBS / J. Doe (Dr. Vance) | Missing 25 Modifier on E/M visit with minor procedure | Append Modifier 25 with chart evidence | Clean & Passed | 99% | |
| CLM-73721 | UHC / R. Smith (Dr. Miller) | Prior Auth # omitted from electronic claim box 23 | Attach Auth # AUTH-88219 from patient chart | Prior Auth OK | 97% | |
| CLM-99285 | Aetna / M. Garcia (Dr. Chen) | ICD-10 R07.9 lacks medical necessity for level 5 code | Update to I20.0 based on documented ECG finding | Code Adjusted | 95% | |
| CLM-45378 | Medicare / T. Taylor (Dr. Patel) | Preventive screening colonoscopy coded as diagnostic | Switch modifier to 33 per ACA preventive rule | Validated | 100% |
HIPAA & Local LLM Security Architecture
Zero cloud exposure architecture keeping patient records strictly within private VPC.
Local LLM Enclave
HIPAA BAA Compliant
Zero PHI Leakage
SOC 2 Type II
AES-256 Encryption
Granular RBAC
Technology Stack
Key technologies powering the production deployment.
LangChain
Ollama (Local Llama 3)
n8n Workflow Automation
Python FastAPI
EHR FHIR / HL7 APIs
PostgreSQL
Docker
Redis Queue
Power BI
AWS Private VPC
What Changed
Key operational and efficiency improvements.
Payer denial rates plummeted from 15% to 3.1% within 90 days of rollout
Claim submission turnaround accelerated from 5 business days to < 12 hours
$3.5 Million in accelerated cash flow and eliminated aging AR backlogs
Billing team efficiency increased by 300% without adding headcount
Complete elimination of preventable unbundling and missing modifier denials
Built for Healthcare Revenue Leaders
Engineered for billing executives, revenue cycle directors, and medical coders.
Chief Financial Officers (CFOs)
Accelerate healthcare cash flow, lower days in AR, and prevent costly payer denial write-offs.
VP of Revenue Cycle Management (RCM)
Empower billing teams with automated code scrubbing and straight-through electronic submission.
Compliance & Audit Directors
Ensure strict coding compliance with defensible medical necessity evidence chains.