Machine Learning Prediction for Postdischarge Falls in Older Adults: A Multicenter Prospective Study.

Objectives: The study aimed to develop a machine learning (ML) model to predict early postdischarge falls in older adults using data that are easy to collect in acute care hospitals. This may reduce the burden imposed by complex measures on patients and health care staff.

Design: This prospective multicenter study included patients admitted to and discharged from geriatric wards at 3 university hospitals and 1 national medical center in Japan between October 2019 and July 2023.

Impact of nurse-led interprofessional work in older patients with heart failure and multimorbidity: A retrospective cohort study.

Background: The number of patients with multimorbidity has increased due to the aging of the global population. Although the World Health Organization has indicated that multimorbidity will be a major medical problem in the future, the appropriate interventions for patients with multimorbidity are currently unknown. This study aimed to investigate whether nurse-led interprofessional work is associated with improved prognosis in heart failure patients with multimorbidity aged ≥65 years who were admitted in an acute care hospital.