Strategies for Creating Robust Patient Groups to Study Diverse Conditions with Electronic Health Records

Abstract

The growth of electronic health record (EHR) databases in size and availability has created an unprecedented opportunity to better understand human health and disease. However, conducting robust EHR studies requires careful filtering criteria and study design, as EHRs pose several challenges that can confound analyses and lead to inaccurate results. Here we review these challenges and make suggestions about how to avoid or adjust for major confounders and biases in common EHR study designs. We further highlight qualities of EHR data that make different diseases more or less feasible for study. These recommendations for conducting research using EHRs will help inform database selection, improve reproducibility of results across the field, and enhance the validity of study results.