Abstract
Rationale: Variation in hospital mortality has been described for coronavirus disease (COVID-19), but the factors that explain these differences remain unclear.
Objective: Our objective was to use a large, nationally representative data set of critically ill adults with COVID-19 to determine which factors explain mortality variability.
Methods: In this multicenter cohort study, we examined adults hospitalized in ICUs with COVID-19 at 70 U.S. hospitals between March and June 2020. The primary outcome was 28-day mortality. We examined patient-level and hospital-level variables. Mixed-effect logistic regression was used to identify factors associated with interhospital variation. The median odds ratio was calculated to compare outcomes in higher- versus lower-mortality hospitals. A gradient-boosted machine algorithm was developed for individuallevel mortality models.
Measurements and Main Results: A total of 4,019 patients were included, 1,537 (38%) of whom died by 28 days. Mortality varied considerably across hospitals (0-82%). After adjustment for patientand hospital-level domains, interhospital variation was attenuated (odds ratio decline from 2.06 [95% confidence interval (CI), 1.73-2.37] to 1.22 [95% CI, 1.00 1.38]), with the greatest changes occurring with adjustment for acute physiology, socioeconomic status, and strain. For individual patients, the relative contribution of each domain to mortality risk was as follows: acute physiology (49%), demographics and comorbidities (20%), socioeconomic status (12%), strain (9%), hospital quality (8%), and treatments (3%).
Conclusions: There is considerable interhospital variation in mortality for critically ill patients with COVID-19, which is mostly explained by hospital-level socioeconomic status, strain, and acute physiologic differences. Individual mortality is driven mostly by patient-level factors.
