We present CLARITY (Clinical Assistant for Routing, Inference and Triage), an AI-driven platform designed to facilitate patient-to-specialist routing, clinical consultations, and severity assessment of patient conditions. Its hybrid architecture combines a Finite State Machine (FSM) for structured dialogue flows with collaborative agents that employ Large Language Model (LLM) to analyze symptoms and prioritize referrals to appropriate specialists. Built on a modular microservices framework, CLARITY ensures safe, efficient, and robust performance, flexible and readily scalable to meet the demands of existing workflows and IT solutions in healthcare. We report integration of our clinical assistant into a large-scale national interhospital platform, with more than 55,000 content-rich user dialogues completed within the two months of deployment, 2,500 of which were expert-annotated for subsequent validation. The validation results show that CLARITY surpasses human-level performance in terms of the first-attempt routing precision, naturally requiring up to 3 times shorter duration of the consultation than with a human.

翻译：本文介绍CLARITY（用于分诊、推理与转诊的临床助手），这是一个旨在促进患者向专科医生转诊、临床咨询及患者病情严重程度评估的人工智能驱动平台。其混合架构将用于结构化对话流程的有限状态机（FSM）与协作智能体相结合，这些智能体利用大语言模型（LLM）分析症状并优先向合适的专科医生转诊。CLARITY构建于模块化微服务框架之上，确保了安全、高效和稳健的性能，并具备灵活性和易于扩展性，以满足医疗保健领域现有工作流程和IT解决方案的需求。我们报告了将该临床助手集成到一个大规模国家级院际平台的情况，在部署的两个月内完成了超过55,000次内容丰富的用户对话，其中2,500次对话经过专家标注以供后续验证。验证结果表明，CLARITY在首次转诊准确率方面超越了人类水平，且咨询时长自然缩短至人工咨询所需时长的三分之一。