Abstract: In this multisite study of anthropometric data extracted from EHRs in an urban low resource setting, we quantified the percentage of biologically implausible values to highlight variation in data validity in clinical care. Review of 410,681 records revealed up to 4.31% of values were implausible. Efforts to standardize data checking at time of data entry of heights and weights at point of care could improve data quality.

Learning Objective 1: Highlight variation in the validity of anthropometric data at time of entry in to electronic health records

Learning Objective 2 (Optional): Identify strategies to validate anthropometric data extracted from EMRs for secondary use

Learning Objective 3 (Optional): Consider strategies to improve the quality of data at the point of entry into the EMR for purposes individual patients


Daryl Wieland (Presenter)
New York City Health+Hospitals/Jacobi

Caroline Jiang, Rockefeller University
Amanda Cheng, Clinical Director's Network
Peter Holt, Rockefeller University
Jan Breslow, Rockefeller University
Dena Moftah, Clinical Director's Network
Jonathan Tobin, Clinical Director's Network

Presentation Materials: