Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been associated with liver impairment and abnormalities in liver function tests. However, associations between hepatic impairment and patient health outcomes have not been well-studied in large cohorts. In this US-based, multicenter retrospective cohort study, we analyze the impact of abnormalities in liver function tests at admission on mortality and adverse health outcomes in patients with laboratory-confirmed COVID-19 infection. Propensity score analysis and a full matching algorithm were used to minimize dissimilarity in covariates thought to impact outcomes of interest and to isolate the effect of liver abnormalities on patient health outcomes. Treatment effect models were then analyzed for sensitivity to hidden covariates. This study demonstrates the usefulness of Cerner’s HealtheDataLab data science ecosystem and de-identified COVID-19 patient cohort for investigating health outcomes related to COVID-19 infection.