语音响应分析代理 (VERAA):利用大型语言模型在SDoH调查中映射语音响应
Rishivardhan Krishnamoorthy1, Vishal Nagarajan1, Hayden Pour1
1University of California San Diego Health, Department of Biomedical Informatics, San Diego, CA.
概括
这项研究引入了一种多语言的对话代理,以收集患者的母语中的健康社会决定因素 (SDoH) 数据,克服电子健康记录 (EHR) 的障碍,改善健康结果预测.
科学领域:
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
- 自然语言处理自然语言处理.
背景情况:
- 健康的社会决定因素 (SDoH) 显著影响健康结果,但在电子健康记录 (EHR) 中经常缺失.
- 有限的英语水平使患者和医疗保健提供者之间存在沟通挑战,阻碍了全面的SDoH数据收集.
研究的目的:
- 设计和开发一个多语言的对话代理,以便在医疗保健环境中有效和包容地收集SDoH数据.
- 为了解决SDoH数据在EHR中缺失的问题,并克服患者沟通中的语言障碍.
主要方法:
- 开发了一种多语言对话代理来进行SDoH调查.
- 代理人在患者的母语中与患者互动,将响应翻译成英语,并使用大语言模型 (LLM) 将响应映射到结构化SDoH调查数据上.
- 该系统可适应医院或家庭环境中的各种测量仪器.
主要成果:
- 会话代理成功地以多种语言收集SDoH数据.
- 患者的自由文本答案被转换为结构化数据,提高SDoH数据的完整性.
- 该LLM有效地映射了对标准化SDoH调查类别的翻译响应.
结论:
- 开发的多语言代理提供了一种新的解决方案,通过克服语言障碍和提高EHR中的数据完整性来丰富SDoH数据.
- 这种方法促进了更具包容性的数据收集,这对于准确的健康结果预测和有针对性的干预至关重要.
- 该工具代表了利用技术在医疗保健中全面采集和利用SDoH数据方面的重大进步.
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