Disease Categorisation Assistant
Classifies medical conditions into clinically relevant disease categories
Description
Challenge:
Accurate classification of medical conditions is critical for underwriting and claims decisions, yet the process is often slowed by inconsistent terminology, manual interpretation, and policy-specific categorization rules. Discrepancies between ICD codes, symptom descriptions, and policy definitions lead to delays, errors, and disputes in coverage and risk assessment. Without automation, insurers face high manual workload, poor consistency, and compliance challenges in applying exclusions or special treatments.
How It Works:
The Disease Categorisation Assistant receives normalized medical condition codes (ICD-10, ICD-11, SNOMED) from upstream modules and maps them into standardized disease categories such as chronic, acute, hereditary, infectious, or lifestyle-related. It references clinical taxonomies, insurer-defined schemas, and policy rulebooks to assign each condition to the right disease bucket. The agent flags conditions requiring manual underwriting or exclusions and outputs structured, standardized categories for downstream systems like underwriting decision engines or claims triage. This ensures risk alignment, policy applicability, and consistent benefit evaluation.
Benefits:
Achieves 85–95% accuracy in automated disease classification
Cuts manual categorization workload by 50–65%
Reduces processing delays from ambiguous inputs by 30–45%
Delivers 100% standardized disease mapping compatible with underwriting and claims rules
Matches 90%+ alignment with expert clinical review
Improves decision-making transparency with audit-ready categorization logs
Minimizes disputes and coverage delays through consistent classification
Resources
Features
The Disease Categorisation Assistant streamlines the classification of medical conditions by integrating standardized taxonomies, NLP-based mapping, and insurer-specific risk rules. It adapts categorization to underwriting and claims workflows while ensuring alignment with policy coverages and exclusions.
Features & Capabilities:
Symptom-to-Category Mapping: Converts condition codes and free-text symptoms into standardized disease categories.
Synonym & Language Expansion: Handles synonyms and multilingual variants for more accurate mapping.
Multiple Symptom Handling: Separately categorizes each condition when multiple inputs are provided.
Policy Coverage Filtering: Flags excluded categories or those needing manual underwriting attention.
Granular Categorization: Adjusts classification detail to fit underwriting vs. claims workflows.
Historical Data Cross-Check: Validates against claimant’s medical history for consistency.
Taxonomy Maintenance: Periodically updates classifications and remaps deprecated codes.
Audit Trail: Records categorization logic and sources for compliance and review.
Operating Blueprint
Knowledge Sources:
Medical Condition Inputs: Raw diagnosis descriptions and extracted document data.
Standard Disease Libraries: ICD-10/11, SNOMED CT, WHO disease grouping guidelines.
Policy & Coverage Rules: Insurer-specific disease schemas, underwriting manuals, exclusion rules.
Clinical Knowledge Bases: UMLS, MedlinePlus, chronic disease registries.
Historical Records: Previously categorized cases and claims outcomes.
Business Rules:
Input Standardization: Accept only normalized condition codes before categorization.
Exclusion Flagging: Highlight categories excluded by policy terms.
Manual Review Rule: Route uncertain or ambiguous conditions to underwriters.
Multi-Category Assignment: Allow conditions to belong to more than one relevant category.
Granularity Rule: Adjust classification depth based on claims vs. underwriting context.
Audit Compliance: Store category decisions with source metadata for traceability.
Tool Workflow:
Receive normalized medical codes or extracted condition data.
Apply taxonomy lookups against ICD, SNOMED, and insurer-defined categories.
Map condition(s) into standardized disease categories.
Apply exclusion rules and manual review flags.
Generate structured outputs (disease category, flags, metadata).
Forward results to underwriting decision engines or claims triage modules.
Badges
Classification
Capabilities
