Year: 2025
Type: conference-paper
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.
Authors: Alok Kumar Sahu, Yi Sun, Eamonn Swanton, Farshid Amirabdollahian, Abi Wren
Institution: University of Hertfordshire
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4412886845