This supplementary appendix provides additional information about the study on hospitalization and mortality among black and white patients with COVID-19. The study used multiple imputation to handle missing data and analyzed clinical characteristics of hospitalized patients. The supplementary methods describe the statistical models used to assess exposure to critical care services. Four models were constructed: (1) a base model with race effect only; (2) a model with age and sex as covariates; (3) a model with pre-admission patient characteristics; and (4) a model with vital signs and laboratory measures at hospital admission. Covariates in models 2 and 3 were selected based on clinical relevance, while those in model 4 were selected based on observed imbalance between critical care and non-critical care patients. Variables with standardized differences > 0.1 were included in the model. The proportional hazards assumption for the Cox models was assessed graphically. Results are presented as hazard ratios with 95% confidence intervals. Table S4 lists the hazard ratios for requiring critical care among patients hospitalized with COVID-19, with different models incorporating various covariates. The study found that certain clinical characteristics were imbalanced between deceased and non-deceased patients, and these imbalances were considered in the models. The analysis aimed to adjust for potential confounding factors and provide a more accurate assessment of the association between race and critical care needs among COVID-19 patients.This supplementary appendix provides additional information about the study on hospitalization and mortality among black and white patients with COVID-19. The study used multiple imputation to handle missing data and analyzed clinical characteristics of hospitalized patients. The supplementary methods describe the statistical models used to assess exposure to critical care services. Four models were constructed: (1) a base model with race effect only; (2) a model with age and sex as covariates; (3) a model with pre-admission patient characteristics; and (4) a model with vital signs and laboratory measures at hospital admission. Covariates in models 2 and 3 were selected based on clinical relevance, while those in model 4 were selected based on observed imbalance between critical care and non-critical care patients. Variables with standardized differences > 0.1 were included in the model. The proportional hazards assumption for the Cox models was assessed graphically. Results are presented as hazard ratios with 95% confidence intervals. Table S4 lists the hazard ratios for requiring critical care among patients hospitalized with COVID-19, with different models incorporating various covariates. The study found that certain clinical characteristics were imbalanced between deceased and non-deceased patients, and these imbalances were considered in the models. The analysis aimed to adjust for potential confounding factors and provide a more accurate assessment of the association between race and critical care needs among COVID-19 patients.