An augmented estimation procedure for EHR-based association studies accounting for differential misclassification.
The ability to identify novel risk factors for health outcomes is a key strength of electronic health record (EHR)-based research. However, the validity of such studies is limited by error in EHR-derived phenotypes. The objective of this study was to develop a novel procedure for reducing bias in estimated associations between risk factors and phenotypes in EHR data.
Author(s): Tong, Jiayi, Huang, Jing, Chubak, Jessica, Wang, Xuan, Moore, Jason H, Hubbard, Rebecca A, Chen, Yong
DOI: 10.1093/jamia/ocz180