OccuTriage: An AI Agent Orchestration Framework for Occupational Health Triage Prediction

Occupational Health (OH) triage is a systematic process for evaluating and prioritising workplace health concerns to determine appropriate care and interventions.This research addresses critical triage challenges through our novel AI agent orchestration framework, Occu-Triage, developed in collaboration with Heales Medical 1 .Our framework simulates healthcare professionals' reasoning using specialized LLM agents, retrieval augmentation with domain-specific knowledge, and a bidirectional decision architecture.Experimental evaluation on 2,589 OH cases demonstrates OccuTriage outperforms single-agent approaches with a 20.16% average discordance rate compared to baseline rates of 43.05%, while matching or exceeding human expert performance (25.11%).The system excels in reducing under-triage rates, achieving 9.84% and 3.1% for appointment and assessor type decisions respectively.These results establish OccuTriage's efficacy in performing complex OH triage while maintaining safety and optimizing resource allocation.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.acl-industry.84
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
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article

OccuTriage: An AI Agent Orchestration Framework for Occupational Health Triage Prediction

Farshid Amirabdollahian, Yi Sun, Alok Kumar Sahu, A. C. Wren et al.
Anomaly Detection Techniques and Applications
article

OccuTriage: An AI Agent Orchestration Framework for Occupational Health Triage Prediction

Farshid Amirabdollahian, Yi Sun, Alok Kumar Sahu, A. C. Wren, Eamonn Swanton
article en

Abstract

Occupational Health (OH) triage is a systematic process for evaluating and prioritising workplace health concerns to determine appropriate care and interventions.This research addresses critical triage challenges through our novel AI agent orchestration framework, Occu-Triage, developed in collaboration with Heales Medical 1 .Our framework simulates healthcare professionals' reasoning using specialized LLM agents, retrieval augmentation with domain-specific knowledge, and a bidirectional decision architecture.Experimental evaluation on 2,589 OH cases demonstrates OccuTriage outperforms single-agent approaches with a 20.16% average discordance rate compared to baseline rates of 43.05%, while matching or exceeding human expert performance (25.11%).The system excels in reducing under-triage rates, achieving 9.84% and 3.1% for appointment and assessor type decisions respectively.These results establish OccuTriage's efficacy in performing complex OH triage while maintaining safety and optimizing resource allocation.

Openalex Percentile: Top 90%
Anomaly Detection Techniques and Applications
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