以人工智能为动力的聊天机器人集成,以提高儿科医院电子健康记录的可访问性
Premasudha Basavaiah Gowramma1, Kiran Kumar1, Monish Shiva Prema2
1Department of Master of Computer Application, Siddaganga Institute of Technology, Tumkur, India.
Scientific reports
|March 13, 2026
概括
一个新的聊天机器人显著减少了医生在电子健康记录 (EHR) 中搜索的时间,减少了40.6%,数据检索准确度提高了25.4%. 这种对话式人工智能提供了一个低成本的解决方案,可以有效地访问儿科电子病历数据.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床数据管理 临床数据管理
背景情况:
- 临床医生面临着大量的时间负担,在电子健康记录 (EHR) 中导航,特别是在资源有限的环境中.
- 现有的EHR系统通常依赖于基本的关键字搜索,导致数据检索效率低下.
- 快速准确地访问结构化儿科电子病历数据对于有效的患者护理至关重要.
研究的目的:
- 评估使用LangChain和GPT-3.5轻量级聊天机器人的有效性,减少搜索时间并提高儿科电子病历数据的检索精度.
- 评估聊天机器人的表现与地区医院环境中的传统关键字搜索系统相比.
- 确定对话式人工智能是否可以改善对结构化临床数据的访问,同时保持患者隐私.
主要方法:
- 使用Flask和Angular开发一个原型EHR系统,与LangChain CSV代理集成,用于动态Python代码生成.
- 使用了1200个儿科接触的数据集,每个数据集有160个变量.
- 与40名临床医生一起进行了标准化的信息搜索任务,比较使用和不使用聊天机器人的表现与基线关键词搜索.
- 使用双尾配对t测试进行统计分析,以评估搜索时间和检索准确度 (精度和回忆) 的变化.
主要成果:
- 聊天机器人将搜索时间的中位数减少了40.6% (从64秒到38秒,p < 0.001).
- F1检索精度提高了25.4% (从0.71到0.89,p < 0.01).
- 该系统在访问结构化儿科电子病历数据的速度和准确性方面显著改进.
结论:
- 像开发的聊天机器人一样,低成本的对话式人工智能可以大幅加快和改善对结构化儿科电子病历数据的访问.
- 聊天机器人技术为提高医疗保健机构临床工作流程效率提供了一种实际解决方案.
- 这种方法通过查询匿名数据来维护数据隐私,而不会将原始患者记录暴露在外部AI模型中.
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