<p>Simulated outcome data example from Phenome Wide Association Study (PheWAS) 
that examines associations between drug exposure and various phenotypes at follow-up 
after the drug exposure. The dataset includes 1505 variables: subject identification 
number ('id'), drug exposure ('exposure'), 3 demographic variables 
('age', 'race', 'gender'), and 1500 phenotypes.</p>

datasets

Process and analyze electronic health record (EHR) data. The 'EHR'
package provides modules to perform diverse medication-related studies using
data from EHR databases. Especially, the package includes modules to perform
pharmacokinetic/pharmacodynamic (PK/PD) analyses using EHRs, as outlined in
Choi, Beck, McNeer, Weeks, Williams, James, Niu, Abou-Khalil, Birdwell, Roden,
Stein, Bejan, Denny, and Van Driest (2020) <doi:10.1002/cpt.1787>. Additional
modules will be added in future. In addition, this package provides various
functions useful to perform Phenome Wide Association Study (PheWAS) to explore
associations between drug exposure and phenotypes obtained from EHR data, as
outlined in Choi, Carroll, Beck, Mosley, Roden, Denny, and Van Driest (2018)
<doi:10.1093/bioinformatics/bty306>.

Leena Choi

Electronic Health Record (EHR) Data Processing and Analysis Tool

Cole Beck

Hannah Weeks

Elizabeth McNeer

Nathan James

Michael Williams

dd function

<p>A data frame with 10000 observations on 1505 variables.</p>

dd: dd

Description

Usage

Arguments

Format

Examples