Advisory Prerequisites: Quantitative training, familiarity with traditional regression methods, basic epidemiologic principles, and working knowledge of R. The course will be instructed with minimal mathematics formulas and will include comprehensive examples to facilitate a bro
Undergraduates are allowed to enroll in this course.
Description: To gain knowledge of the process of cleaning and abstracting EHR data to create analytic datasets, attain a broader understanding the secondary use of EHR data for research, with a focus on epidemiologic principles including the role of study design, bias, and generalizability
Learning Objectives: This short course will offer an overview of modern analytical methods and research applications using EHR data, with a specific focus on epidemiologic inferences. Upon completion of the course, participants will i) gain knowledge of the process of cleaning and abstracting EHR data to create analytic datasets, ii) attain a broader understanding of the opportunities and challenges of the secondary use of EHR data for research, with a focus on epidemiologic principles including the role of study design, bias, and generalizability, iii) explore and gain hands-on experience using EHRs from Michigan Medicine, and iv) be prepared to generate and further explore new questions and perspectives.
