Medical Document & Evidence Agent
Extract and validate critical medical document data for accurate, compliant claim processing
Description
Challenge:
Claims processing often relies on diverse, unstructured medical documents like prescriptions, discharge summaries, lab reports, and bills. Manual review is slow, error-prone, and may miss inconsistencies, missing evidence, or fraudulent submissions. Incomplete or misaligned documentation causes delays, incorrect payouts, and increases operational workload for claims teams. Without automated validation, insurers risk compliance breaches and poor claimant experience.
How It Works:
The Medical Document & Evidence Agent uses OCR and NLP to extract structured information from all submitted medical documents. It validates extracted data against policy rules, claim declarations, and treatment guidelines. The agent flags missing or inconsistent information, verifies document authenticity, and checks alignment with the claimed event. Structured, verified outputs are then passed to claim reconciliation or human handlers, ensuring accuracy and compliance.
Benefits:
Achieves 92–97% accuracy in extracting structured data from medical documents
Reduces manual document review effort by 40–60%
Ensures complete, claim-aligned evidence for every case
Detects inconsistencies, tampering, and duplicate submissions early
Speeds up processing with <20-second average validation per document
Resources
Features
The agent guarantees every submitted medical document is complete, authentic, and aligned with the claim and policy context.
Features & Capabilities:
Document Extraction: OCR converts PDFs, scanned reports, and images into structured text
Field Recognition: NLP identifies diagnosis, treatment, costs, doctor, and hospital information
Treatment–Document Mapping: Matches documents to specific treatments (e.g., surgery → discharge + operative notes)
Completeness Validation: Checks for date, doctor signature, hospital seal, and mandatory fields
Authenticity Verification: Detects tampering and cross-checks handwritten or scanned documents
Policy Alignment: Validates documents against claim type and required evidence
Duplicate & Fraud Detection: Flags previously submitted or suspicious documents
Classification: Categorizes documents as Valid, Incomplete, Tampered, or Suspicious
Audit Logging: Maintains tamper-proof logs for compliance and dispute resolution.
Operating Blueprint
Knowledge Sources:
Uploaded Documents: PDFs, images, scanned reports with metadata
Medical Term Ontology: ICD/SNOMED codes for diagnosis, procedures, and clinical concepts
Claim Record: Treatment stage, declared costs, claim type
Policy Document Rules: Required document sets per claim type or procedure
Historical Database: Past submissions for duplication and fraud checks
Business Rules:
Document Type Rule: Mandatory document types per claim (e.g., discharge summary for surgery)
Completeness Rule: Must include date, signature, seal, and invoice details
Authenticity Rule: Handwritten or scanned documents verified for tampering
Freshness Rule: Documents must be within defined validity limits
Claim Alignment Rule: Diagnosis/treatment must match declared claim information
Duplicate/Fraud Rule: Compare against historical claims and public databases
Tool Workflow:
Receive uploaded documents (PDF/JPG)
Extract raw text via OCR
Apply NLP to identify key fields (diagnosis, treatment, amount, hospital, doctor)
Map content to declared treatment in claim
Validate completeness, authenticity, and mandatory elements
Classify documents: Valid, Incomplete, Tampered, or Suspicious
Log results and pass structured outputs to claim drafting or human review
Badges
Classification
Capabilities
