7 Clinical Trials for Various Conditions
This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict patient deterioration throughout a patient's admission. This algorithm was then validated in a validation cohort.
This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict the likelihood of 30-day readmission throughout a patient's admission. This algorithm was then validated in a validation cohort.
This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict length of stay throughout a patient's admission. This algorithm was then validated in a validation cohort.
This study examines the implications of providing hospital-level care in rural homes.
This study examines the implications of providing remote physician care to home hospitalized patients compared to usual home hospital care with in-person/in-home physician visits.
The investigators propose a home hospital model of care that substitutes for treatment in an acute care hospital. Limited studies of the home hospital model have demonstrated that a sizeable proportion of acute care can be delivered in the home with equal quality and safety, reduced cost, and improved patient experience.
The investigators propose a home hospital model of care that substitutes for treatment in an acute care hospital. Limited studies of the home hospital model have demonstrated that a sizeable proportion of acute care can be delivered in the home with equal quality and safety, reduced cost, and improved patient experience.