Background: Clinically stable inpatients may receive potentially unnecessary care, such as overnight vital sign assessment. Nighttime vital signs can disrupt sleep and adversely affect patient satisfaction and contribute to delirium. However, it may be difficult for individual clinicians to determine which patients could safely forego overnight vital signs. Purpose: We developed a predictive algorithm designed [...]

Background: Clinically stable inpatients may receive potentially unnecessary care, such as overnight vital sign assessment. Nighttime vital signs can disrupt sleep and adversely affect patient satisfaction and contribute to delirium. However, it may be difficult for individual clinicians to determine which patients could safely forego overnight vital signs. Purpose: We developed a predictive algorithm designed [...]

Background: Sepsis is one of the top causes of inpatient mortality and rapid detection presents numerous challenges. In March, 2016, an interdisciplinary team consisting of top clinicians, data scientists and machine learning experts at a large academic medical center (AMC) embarked on an innovation pilot to develop a novel machine learning model to detect sepsis. [...]