© 2019 Elsevier Inc. Objective: Delirium is acute disorder of attention and cognition. We conducted an observational study using a hospital-wide database to validate three delirium prediction models that were developed to predict prevalent delirium within the first day of hospitalization after ED visit. Methods: This was a retrospective cohort study at the academic medical center to evaluate the predictive ability of three previously developed prediction models for delirium from 2014 to 2017. We included patients aged 65 years and older who were hospitalized from ED. Nurses used the Delirium Observation Screening Scale (DOSS) twice daily while hospitalized. We extracted variables to examine the three prediction models with a positive DOSS screen within the first day of admission. The predictive ability was summarized using the area under the curve (AUC). Results: We identified 2582 visits with a positive DOSS screen and 877 visits with a diagnosis of delirium from ICD9/10 codes among 12,082 encounters. The AUC of these prediction models ranged from 0.71 to 0.80 when predicting a positive DOSS screen, and 0.68 to 0.72 when predicting a ICD9/10 diagnosis of delirium. In our cohort, the delirium risk score which uses the cutoff of positive or negative predicted DOSS positive delirium with the AUC of 0.8 (p <.0001). The model demonstrated the sensitivity and the specificity of 91.2 (95% CI 90.0–92.3) and 50.3 (95% CI 49.3–51.3). Conclusion: In this study, the delirium risk score had the highest predictive ability for prevalent delirium defined by a positive DOSS within the first day of hospitalization.