Objective: Hospitals vary widely in ICU admission rates across numerous medical diagnoses. The extent to which variability in ICU use is specific to individual diagnoses or is a function of the hospital, regardless of disease, is unknown. Design: Retrospective cohort study. Setting: A total of 1,120 acute care hospitals with ICU capabilities. Patients: Medicare beneficiaries 65 years old or older admitted for five medical diagnoses (acute myocardial infarction, congestive heart failure, stroke, pneumonia, and chronic obstructive pulmonary disease) and a surgical diagnosis (hip fracture treated with arthroplasty) in 2010. Interventions: None. Measurements and Main Results: We used multilevel models to calculate risk- and reliability-adjusted ICU admission rates, examined the correlation in ICU admission rates across diagnosis and calculated intraclass correlation coefficients and median odds ratios to quantify the variability in ICU admission rate that was attributable to hospitals. We also examined the ability of a high ICU-use hospital for one condition to predict high ICU use for other conditions. We identified 348,462 patients with one of the eligible conditions. ICU admission rates were positively correlated within hospitals for included medical diagnoses (r range, 0.38-0.59; p < 0.01). The top hospital quartile of ICU use for congestive heart failure had a sensitivity of 50-60% and specificity of 79-81% for detecting top quartile hospitals for each other conditions. After adjustment for patient and hospital characteristics, hospitals accounted for 17.6% (95% CI, 16.2-19.1%) of variability in ICU admission, corresponding to a median odds ratio of 2.3, compared to 25.8% (95% CI, 24.5-27.1%) and median odds ratio 2.8 for diagnosis. This suggests a patient with median baseline risk of ICU admission would more than double his/her odds of ICU admission if moving to a higher utilizing hospital. Conclusions: Hospitals account for a significant proportion of variation independent of measured patient and hospital characteristics, suggesting the need for further work to evaluate the causes of variation at the hospital level and potential consequences of variation across hospitals.