Medical Report Diagnosis Extractor Agent
Translate medical conditions into standardized ICD codes for automation
Description
Challenge:
Medical reports often contain unstructured clinical text, making manual extraction of diagnoses slow, error-prone, and inconsistent. Misinterpretation or delays in coding can impact claim adjudication, underwriting risk assessment, and regulatory compliance.
How It Works:
This agent processes medical documents—including discharge summaries, lab reports, imaging notes, and physician assessments—using OCR, NLP, and medical ontologies. It identifies primary, secondary, and comorbid diagnoses, maps them to ICD-10/ICD-11 codes, and validates them against policy coverage and treatment data. Ambiguous or unsupported terms are flagged for manual review, ensuring high accuracy. Structured JSON outputs are generated for seamless integration with claims, underwriting, and compliance workflows.
Benefits:
90–95% accuracy in automated ICD code mapping
Reduces manual coding workload by 70–80%
Cuts extraction time per report from 15–20 minutes to under 1 minute
Ensures 95%+ alignment with policy coverage rules
Standardizes diagnosis data for claims and underwriting
Supports faster adjudication and improved compliance
Features
Automates the extraction and codification of medical diagnoses from unstructured reports, providing validated, policy-aligned, structured data for downstream workflows.
Features & Capabilities:
Document Intake: Accept PDFs, Word files, or image uploads
OCR/NLP Extraction: Detect diagnosis-related text in medical reports
Term Identification: Capture primary, secondary, and comorbid conditions
ICD Mapping: Map diagnoses to ICD-10/ICD-11 codes
Coverage Validation: Check alignment with policy coverage and exclusions
Ambiguity Handling: Route low-confidence extractions for manual review
Synonym Normalization: Convert clinical synonyms to standard terminology
Output Generation: Produce structured JSON for claims, underwriting, and compliance pipelines
Operating Blueprint
Knowledge Sources:
ICD-10/ICD-11 Code Repository
SNOMED CT, UMLS, MedDRA for synonyms and terminology
Hospital discharge summaries, lab reports, and physician notes
Claims history and policy coverage rules
Clinical-treatment mapping dictionaries
Business Rules:
Primary Diagnosis Identification: Map the first or explicitly stated condition
Multi-Diagnosis Handling: Capture comorbidities separately
**Synonym Expansion: **Normalize medical terms (e.g., “heart attack” → “acute myocardial infarction”)
Coverage Match: Ensure diagnoses align with policy coverage
Exclusion Check: Flag non-covered or excluded illnesses
Ambiguity Handling: Manual review for low-confidence extractions
Claim Alignment: Ensure diagnosis corresponds with claim type
Code Validation: Only valid ICD codes accepted
Tool Workflow:
Document Intake → OCR/NLP extraction → Term identification
ICD Mapping → Policy and treatment validation → Ambiguity flagging
Output → Structured JSON → Route to claims, underwriting, and compliance
Audit Logging → Capture extraction, mapping, and validation steps
Badges
Classification
Capabilities
