在ICU电子健康记录数据中的隐性偏差:临床变量的测量频率和缺失数据率
Junming Shi1, Alan E Hubbard1, Nicholas Fong2
1Division of Biostatistics, University of California Berkeley, Berkeley, CA, USA.
BMC medical informatics and decision making
|July 2, 2025
概括
电子健康记录 (EHR) 数据收集的系统差异存在于患者人口统计学中,并且与ICU死亡率有关. 分析这些测量模式是提高医疗保健公平性和预测准确性的关键.
科学领域:
- 关键护理医学 关键护理医学
- 医疗信息学 医疗信息学
- 健康 公平 研究 健康 公平 研究
背景情况:
- 电子健康记录 (EHR) 数据收集中的系统差异,以临床变量测量和记录在人口群体中的非随机模式为特征,可以反映隐含的偏见并影响患者的结果.
- 识别和减轻这些偏见对于实现公平的医疗保健服务至关重要.
- 本研究侧重于测量模式,定义为测量频率和缺失数据速率的相互作用,以调查这些差异.
研究的目的:
- 开发一个分析框架,以了解EHR数据中的测量模式.
- 评估测量模式与人口因素之间的关联.
- 评估这些模式对预测住院死亡率的影响.
主要方法:
- 一项使用MIMIC-III数据库 (超过40,000名ICU患者) 的回顾性队列研究.
- 测量模式的分析 (频率和缺失数据率) 来自成人ICU患者的EHR数据,停留时间超过24小时.
- 使用有针对性的机器学习 (TML) 方法来评估人口差异 (年龄,性别,种族/种族),同时控制疾病严重程度等混因素.
主要成果:
- 在ICU住院的前24小时内,观察到测量模式的显著人口差异.
- 老年患者的体温测量更频繁;男性的体温数据比女性少.
- 种族差异包括与黑人和西班牙裔患者相比,白人患者的血压和SpO2测量更频繁. 仅测量模式就预测了ICU死亡率,其AUC为0.76.6.
结论:
- 在ICU EHR数据中的测量模式与患者人口统计和ICU死亡率有显著的关联.
- 对缺失数据和测量频率的分析为监测实践和系统医疗保健差异提供了洞察力.
- 了解这些差异对于提高医疗保健公平性和完善重症监护预测模型至关重要.
关键词:
偏差检测 偏差检测 偏差检测关键的护理关键的护理数据的完整性数据的完整性电子健康记录 (EHR) 是一种电子医疗记录.卫生公平性健康公平性医疗保健应用程序的应用程序隐含的偏见 隐含的偏见在MIMIC-III数据集中.测量频率的测量频率是什么系统的差异是系统的差异.更多相关视频
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