评估电子健康记录数据质量对识别2型糖尿病患者的影响:横截面研究
Priyanka Dua Sood1, Star Liu2, Harold Lehmann1,2
1Bloomberg School of Public Health, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD, 21205, United States, 1 443-287-8264.
JMIR medical informatics
|August 27, 2024
概括
电子健康记录 (EHR) 数据质量问题显著影响使用可计算的表型识别2型糖尿病 (T2D) 患者的识别. 数据完整性,准确性和及时性的变化减少了患者队列的大小,并跨定义重叠.
科学领域:
- 医疗信息学 医疗信息学
- 临床数据科学 临床数据科学
- 慢性疾病管理 慢性疾病管理
背景情况:
- 电子健康记录 (EHR) 对医疗保健数据越来越重要,需要对数据质量进行强有力的评估.
- 准确识别患者群体,如2型糖尿病患者,对于临床研究和操作决策至关重要.
- 现有的慢性疾病可计算的表型定义可能对EHR数据质量变化敏感.
研究的目的:
- 评估EHR数据质量问题的影响,用于识别2型糖尿病 (T2D) 分母群的可计算表型的性能.
- 评估表型的变化和强度如何影响患者队列识别.
主要方法:
- 在约翰霍普金斯医疗机构 (2017-2019) 的约208,000名T2D患者的EHR数据的回顾性分析.
- 包括T2D的4个已发表的表型和1个专家定义的表型.
- 在诊断,药物和实验室数据类型中模拟数据质量问题 (不完整性,不准确性,及时性).
主要成果:
- 在不同的表型中观察到较低的人口重叠 (<23%).
- 模拟数据不完整性,不准确性和及时性问题显著减少了每个表型的确定的患者数量.
- 在诱导的数据质量退化下,表型性能在很大程度上存在差异.
结论:
- 电子病历数据质量显著影响使用可计算的表型可靠地识别T2D患者队列的能力.
- 研究结果强调需要共同,强大的T2D表型定义,以确保临床信息学和医疗保健管理的一致性.
- 这项研究为未来的努力提供了信息,以标准化可计算的表型,以改善临床研究和操作决策.
关键词:
这就是为什么DM DM DM欧洲人权理事会 欧洲人权理事会电子人权 (EHRs) 是一种电子人权.慢性病 慢性病是一种慢性病.临床研究和临床试验可以计算的可计算.可计算的表型.数据质量数据质量数据质量数据科学数据科学数据类型:诊断数据,药物数据,实验室数据.糖尿病 糖尿病患者 糖尿病患者糖尿病的糖尿病患者.诊断 诊断 诊断 诊断 诊断 诊断诊断 诊断 诊断 诊断诊断 诊断 诊断 诊断 诊断 诊断诊断 诊断 诊断 的 诊断 诊断 诊断 诊断 的 诊断诊断 诊断 诊断 诊断 诊断电子健康记录 电子健康记录医院系统 医院系统标识 标识 标识 标识 标识识别 识别 识别 识别现象型 现象型 是一种现象型.现象类型 现象类型现象型的表型现型定制 现型定制 现型定制记录记录记录记录记录记录记录记录 记录 记录 记录 记录第2类型 2型 2型2 型糖尿病 2 型糖尿病相关概念视频
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