Harvard Catalyst Journal Club on Mar. 2: Missing Data Challenges in EHR-Based Studies of COVID & Long COVID (Tanayott Thaweethai, PhD)

Tanayott Thaweethai, PhD will lead a journal club with Harvard Catalyst on Wed 3/2 from 1-2pm.

Title: Missing Data Challenges in Electronic Health Records-Based Studies of COVID and Long COVID

Abstract: Since the beginning of the COVID-19 pandemic, researchers have repeatedly turned to electronic health records (EHR) to rapidly answer complex questions about the short and long-term consequences of SARS-CoV-2 infection. However, because EHR are not collected for research purposes, observational studies using EHR are subject to various challenges and biases, including bias due to missing data. Standard missing data methods generally fail to address the complex nature of EHR data, particularly the interplay of numerous decisions by patients, physicians, and insurers that collectively determine whether “complete” data is observed. Tanayott Thaweethai, PhD, Massachusetts General Hospital, will discuss some statistical methods for handling bias due to missing data in the EHR setting, and conclude with an introduction to a semi-supervised learning technique for handling the “positive unlabeled” problem of phenotyping individuals based on the presence or absence of clinical codes.

The talk will occur on Wednesday March 2, 2022, 1-2pm.

Register here.