在现实世界诊所中实施基于诊所的数据采集
Gabriel Martz1, Isshori Gurung2, Ya-Huei Li1
1Hartford HealthCare, Jefferson Building, Suite 607, 80 Seymour St, Hartford, CT 06102, United States.
Epilepsy & behavior : E&B
|October 3, 2025
概括
在治疗中实施电子健康记录需要临床医生的参与,以成功获取结构化数据. 优化工作流程和患者调查是提高数据质量和确保公平的患者代表性的关键.
科学领域:
- 医疗信息学 医疗信息学
- 临床数据管理 临床数据管理
- 治疗的护理
背景情况:
- 在日常护理过程中采集结构化的临床数据是具有挑战性的,但对于学习健康系统 (LHS) 来说至关重要.
- 通过数据驱动的洞察力和基于证据的指导,LHS旨在改善患者护理.
- 一个中心试图通过软件来增强数据捕获,用于患者调查和临床医生数据输入.
研究的目的:
- 评估在中心实施软件系统用于结构化临床数据捕获的最初18个月的结果.
- 评估临床医生数据输入和患者调查完成率.
- 识别与成功数据采集和调查完成相关的因素.
主要方法:
- 实施一个软件系统,用于在诊所访问期间进行患者调查和离散的临床医生数据输入.
- 分析了18个月内1,664名患者2779次访问的数据.
- 评估临床医生的参与和患者调查完成率,根据人口统计和访问类型进行子组分析.
主要成果:
- 在59.5%的访问中,临床医生手动输入数据,在48.9%的访问中,完全输入数据域,主要由少数临床医生驱动.
- 在16.2%的访问中完成了患者调查,54.7%的访问中完成了至少一个调查.
- 白人,非西班牙裔,男性患者,医疗补助/自付保险和随访的临床医生入门率较高. 更高的调查完成率与英语说话者,面对面访问,新患者和私人保险有关.
结论:
- 结构化的临床数据捕获是可行的,有了强大的临床医生参与和优化的工作流程.
- 需要努力确保在不同患者群体中获得公平的数据.
- 系统实施必须解决边缘化群体完成调查的潜在障碍,以避免偏见的数据.
相关概念视频
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