Use of Different Inclusion Criteria to Compare COVID-19 Hospital Admission Rates by Race and Ethnicity: A Cohort Study
Joshua Longcoy, Zeynep Isgor, Sumihiro Suzuki, Elizabeth Lynch, Heng Wang, David Ansell, Tricia J. Johnson

TL;DR
This study shows how different inclusion criteria in medical records can lead to conflicting results when comparing hospitalization rates for different races during the COVID-19 pandemic.
Contribution
The study demonstrates how sample selection methods affect observed racial disparities in hospitalization rates for COVID-19.
Findings
Using all positive tests showed higher hospitalization odds for Black and Hispanic patients compared to White patients.
Using only ED-positive tests showed higher hospitalization odds for White patients.
Results matched findings from other studies using similar inclusion criteria.
Abstract
Background/Objectives: Reports documenting racial disparities in COVID-19 hospitalization rates from electronic medical record data have used different sample selection methods. Studies including all individuals with a positive COVID-19 test may be vulnerable to misclassification bias if hospitalization status is not captured for all individuals (i.e., if they went to a non-study hospital). A few studies have used only patients who tested positive in the ED and have found different results. In this study, we explore the implications of using different sets of inclusion criteria for analyses that compare COVID-19 hospital admissions by race and ethnicity. Methods: Two separate data sets were created by applying the two different COVID-19 testing inclusion criteria to medical records data from a single academic health system. We used logistic regression to compare the odds of COVID-19…
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Taxonomy
TopicsCOVID-19 Clinical Research Studies · Food Security and Health in Diverse Populations · COVID-19 and healthcare impacts
