通过数据来源评估结构化电子健康记录数据与参考术语的协调性和数据完整性
Keith Marsolo1,2, Lesley Curtis1,2, Laura Qualls2
1Department of Population Health Sciences Duke University School of Medicine Durham North Carolina USA.
将电子健康记录 (EHR) 数据与参考术语协调一致,揭示了映射错误和数据完整性问题. 使用多个数据来源增强了EHR数据分析的稳定性.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 临床数据管理 临床数据管理
背景情况:
- 结构化的电子健康记录 (EHR) 数据对于临床研究至关重要.
- 对参考术语的协调和数据完整性的评估对于数据质量至关重要.
- 不同数据合作伙伴 (DP) 之间的EHR数据的变化需要严格的评估.
研究的目的:
- 评估EHR数据中的实验室结果和药物的协调,以参考术语.
- 描述协调问题的严重性,并确定数据完整性的问题.
- 评估数据来源对完整性评估的影响.
主要方法:
- 向三个数据合作伙伴 (DP) 分发了协调和完整性查询.
- 检查了前200个实验室结果和药物,以获得协调异常值和总结统计数据.
- 分析了四个感兴趣的条件的数据完整性,按时间,护理环境和来源分层.
主要成果:
- 中位数代码关联通常符合预期,但确定了DP特定的协调异常值.
- 根据数据来源,观察到患者概念百分比的显著差异.
- 协调查询发现了映射错误,过于具体的代码和"零"代码问题.
结论:
- 在临床数据模型 (CDM) 中存在协调错误,尽管并不总是普遍存在.
- 多个数据来源类型提供比单个来源更强大的完整性结果.
- 如果在CDM中代表了EHR数据完整性的问题,则来源信息是确定EHR数据完整性的关键.
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