Big Data Decision-Making and Racial Disparities: A Case Study Among COVID-19 Inpatient Visits

The COVID-19 pandemic has had a disproportionate impact on certain racial and ethnic groups, resulting in significant health outcome disparities. The National COVID Cohort Collaborative (N3C) provides a valuable resource for exploring these disparities through big data analytics. This study belongs to a broader work that examines decisions made during data processing and their impact on the analyses performed. Central to our analysis is the introduction of the Continuous Inpatient Encounter (CIE) concept—a novel method we propose for aggregating inpatient visits. By utilizing big data analytics, we aim to identify potential disparities in CIE rates among different racial groups. The results of this study are critical for enhancing the equity of data-driven decision-making in healthcare and for addressing the racial disparities observed in COVID-19 outcomes.