通过自然语言处理揭示的痴呆症诊断轨迹和临床实践模式的现实世界见解:开发和可用性研究
Hunki Paek1, Richard H Fortinsky2, Kyeryoung Lee1
1IMO Health, Rosemont, IL, United States.
JMIR aging
|February 25, 2025
概括
从记忆丧失投诉到痴呆症诊断的中位时间是342天. 大约25%的患者在诊断前接受了增强认知的药物,受投诉细节和护理人员关系的影响.
科学领域:
- 神经学 神经学
- 老年病的医生 老年病的医生
- 医疗信息学 医疗信息学
背景情况:
- 了解痴呆症的发展轨迹和门诊临床模式对于有效的患者管理至关重要.
- 关于从最初的记忆丧失投诉到正式的痴呆症诊断的进展,知识有限.
- 这项研究解决了了解门诊患者痴呆症患者临床旅程的差距.
研究的目的:
- 在门诊护理中确定初始记忆丧失投诉和痴呆症诊断之间的时间间隔.
- 评估在痴呆症诊断之前接受认知增强药物的患者比例.
- 确定影响诊断时间和药物处方的患者和提供者特征.
主要方法:
- 使用大型门诊电子健康记录 (EHR) 数据库 (2010-2018) 的回顾性队列研究.
- 采用基于深度学习的自然语言处理 (NLP) 管道,从EHR数据中提取临床信息.
- 应用描述性统计,线性和后勤回归用于数据分析.
主要成果:
- NLP管道实现了高性能,精度,回忆和F1分数分别为0.97,0.93和0.95.
- 从第一个记忆丧失投诉到痴呆症诊断的中位时间为342天 (IQR 200-675).
- 大约25.1%的患者在诊断前接受了增强认知的药物,受投诉特征和护理人员关系的影响.
结论:
- 以NLP为指导的分析为门诊患者的痴呆症诊断途径和药物治疗实践提供了宝贵的见解.
- 这些发现可以增强临床决策,并改善患有记忆障碍的人的患者护理.
- 了解这些轨迹对于优化痴呆症管理策略至关重要.
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