Towards augmenting structured EHR data: a comparison of manual chart review and patient self-report
Towards augmenting structured EHR data: a comparison of manual chart review and patient self-report
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发表时间：
2019
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通讯作者：
N. Weiskopf;A. Cohen;Joe Hannan;Thad Jarmon;D. Dorr
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作者：
N. Weiskopf;A. Cohen;Joe Hannan;Thad Jarmon;D. Dorr
结构化电子健康记录（EHR）数据通常用于质量测量和改进、临床研究和其他次要用途。然而，这些数据存在质量问题。增强结构化EHR数据以提高数据质量，从而提高从这些数据中得出的结论的可靠性和有效性可能是有价值的。本文重点关注与心血管护理相关的五种诊断，认为两种替代数据源的附加值：手动图表摘要和患者自我报告。我们评估了结构化EHR问题列表数据、抽象EHR数据和患者自我报告之间的总体一致性;并探讨了这些来源之间不一致的可能原因。我们的研究结果表明，图表摘要和患者自我报告包含的诊断比问题列表多得多，但它们捕获的信息是不同的。收集和验证自我报告的医疗数据的方法需要进一步考虑和探索。
Structured electronic health record (EHR) data are often used for quality measurement and improvement, clinical research, and other secondary uses. These data, however, are known to suffer from quality problems. There may be value in augmenting structured EHR data to improve data quality, thereby improving the reliability and validity of the conclusions drawn from those data. Focusing on five diagnoses related to cardiovascular care, this paper considers the added value of two alternative data sources: manual chart abstraction and patient self-report. We assess the overall agreement between structured EHR problem list data, abstracted EHR data, and patient self- report; and explore possible causes of disagreement between those sources. Our findings suggest that both chart abstraction and patient self-report contain significantly more diagnoses than the problem list, but that the information they capture is different. Methods for collecting and validating self-reported medical data require further consideration and exploration.