Towards augmenting structured EHR data: a comparison of manual chart review and patient self-report

Nicole Weiskopf, Aaron M. Cohen, Joely Hannan, Thad Jarmon, David Dorr

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)903-912
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2019
StatePublished - 2019

ASJC Scopus subject areas

  • Medicine(all)

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