Background: Although 88% of inpatients with falls do not sustain injuries, those with fall-related injuries experience limitations in activities of daily living, residual disabilities, and additional medical costs. Therefore, predicting fall-related injuries is crucial. We previously developed a prediction model for fall-related injuries, the Saga Fall Injury Risk Model (SFIRM), in an acute care hospital [...]

Background: Delirium, an acute neuropsychiatric syndrome marked by fluctuating disturbances in attention, cognition, and consciousness, is prevalent among older hospitalized cancer patients. The Mayo Delirium Prediction (MDP) tool, designed to predict delirium risk in older adults using electronic health record (EHR) data, may help identify individuals at increased risk, thus offering valuable insights for targeted [...]