Bhramar Mukherjee will speak on "Using Electronic Health Records and Phenome-Wide Association Studies for COVID-19 Research."
Electronic Health Records linked with other auxiliary data sources hold tremendous potential for conducting real-time actionable research. However, one has to answer two fundamental questions before conducting inference: "Who is in my study?" and "What is the target population of Inference?" Without accounting for selection bias, one can quickly produce fast but inaccurate conclusions.
In this talk, I will discuss large-scale association studies across multiple phenotypes, namely Phenome-wide association studies (PheWAS) that have gained traction in the genetics and medical informatics world. I will present several applications of this tool in genetics, in cancer and for identifying risk factors for COVID-19 hospitalization and mortality. I will further discuss a statistical framework for jointly considering selection bias and phenotype misclassification in such analyses. This is joint work with Lars Fritsche, Lauren Beesley and Maxwell Salvatore at the University of Michigan School of Public Health.
Register in advance for this webinar: https://bit.ly/3kGx9Bs