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.

Learning Objective: Understand the trade-offs between patient self-report and EHR-derived data.


Nicole Weiskopf (Presenter)
Oregon Health & Science University

Aaron Cohen, Oregon Health & Science University
Joely Hannan, Oregon Health & Science University
Thad Jarmon, Oregon Health & Science University
David Dorr, Oregon Health & Science University

Presentation Materials: