Practical Solutions for Working with Electronic Health Records Data — Professional Development Continuing Education Course
ASA, Section on Statistics in Epidemiology
This short course will introduce participants to the basic structure of EHR data and provide a practical set of tools to analyze this rich data resource through a combination of lecture and hands-on exercises in R. The first part of the course will cover issues related to the structure and quality of EHR data, including data types and methods for extracting variables of interest; sources of missing data; error in covariates and outcomes extracted from EHR data; and data capture considerations such as informative visit processes and medical records coding procedures. In the second half of the course, we will discuss statistical methods to mitigate data quality issues arising in EHR, including missing data, error in EHR-derived covariates and outcomes, and data integration across multiple clinical practices. R code will be provided for implementation of the presented methods, and hands-on exercises will be used to compare results of alternative approaches. This short course is of interest to researchers without prior experience working with EHR data as well as more experienced individuals interested in learning practical solutions to some common analytic challenges.
Instructor(s): Rebecca Hubbard, University of Pennsylvania; Yong Chen, University of Pennsylvania
