Medical Resume Agent
Digitize medical resumes, map diagnoses to ICD-10 codes
Description
Challenge:
Unstructured hospital resumes, discharge summaries, and clinical reports contain critical patient information that is often inconsistent, multilingual, or full of abbreviations. Manual extraction leads to incomplete records, coding errors, and delays in claim adjudication or underwriting. Inaccurate or missing ICD-10 coding introduces compliance risks, slows decision-making, and increases operational overhead.
How It Works:
The Medical Resume Agent parses uploaded medical documents using OCR and NLP, extracting mandatory fields such as patient demographics, hospitalization dates, symptoms, diagnoses, treatments, surgeries, and recovery timelines. Non-English or non-Bahasa content is translated to English, while English/Bahasa text is preserved. Abbreviations and OCR errors are normalized using a medical dictionary. Each diagnosis is mapped to the most specific ICD-10 code, with enrichment for sub-categories and descriptive details. The agent generates structured, audit-ready JSON outputs that integrate seamlessly into claims, underwriting, and compliance workflows.
Benefits:
Extracts and structures multi-language medical resumes with 85–95% field-level accuracy
Maps diagnoses to ICD-10 sub-category codes with 90%+ correctness
Reduces manual coding effort by 60–70%
Cuts document processing time from ~15 minutes manually to under 1 minute
Ensures fully standardized date formats and audit-ready records for compliance
Supports downstream automation for claims, fraud checks, and analytics
Resources
Features
The Medical Resume Agent ensures every uploaded medical document is digitized, normalized, and mapped to standard codes, delivering precise, structured, and audit-ready patient records for claims and underwriting workflows.
Features & Capabilities:
Document Ingestion & OCR: Reads PDFs, normalizes orientation, and extracts text accurately
Field Extraction: Captures mandatory patient and hospitalization information, clinical findings, treatments, and surgeries
Multi-Language Handling: Preserves English/Bahasa, translates other languages (e.g., Chinese) to English
Medical Normalization: Expands abbreviations and corrects OCR errors using a medical dictionary
Diagnosis Mapping: Extracts primary and secondary diagnoses and maps to ICD-10 codes at the sub-category level
Surgery Mapping: Expands abbreviations and maps procedures to surgeon groups and codes
Data Validation: Ensures completeness, standardizes dates, and flags empty or unclear fields
Structured Output: Generates JSON in strict snake_case schema, ready for downstream systems
Audit Logging: Records source, translations, and coding rationale for regulatory compliance
Operating Blueprint
Knowledge Sources:
Hospital discharge summaries, medical resumes, and clinical reports
ICD-10 code repository and coding standards
Multilingual medical dictionary and terminology normalization guides
Regulatory formats and document validation guidelines
Business Rules:
Date Validation Rule: Output hospitalization dates in dd/mm/yy or dd/mm/yyyy format
Language Rule: Translate only non-English/Bahasa text; preserve English/Bahasa
Diagnosis Extraction Rule: Use only “Diagnose:” and “Primary Diagnose:”; leave null if missing
ICD-10 Mapping Rule: Map to the most specific sub-category; leave null if unclear
Surgery Mapping Rule: Expand abbreviations and map using vector search
Null Enforcement Rule: Return empty string or null for unreadable or missing fields
Output Schema Rule: Generate JSON with exact snake_case keys as specified
Tool Workflow:
Parse and OCR uploaded medical documents
Extract mandatory fields including patient, hospitalization, clinical findings, treatments, and surgeries
Translate non-English content; normalize abbreviations and OCR errors
Map diagnoses to ICD-10 codes and surgeries to surgeon groups/codes
Standardize dates and validate completeness
Generate structured JSON output and log audit details
Deliver data for claims, underwriting, and compliance workflows
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