In one of the largest studies of its kind, researchers found that up to 80% of emergency department visits and more than one-third of hospitalizations in severely impaired and terminally ill nursing home residents were potentially avoidable. Common causes included UTIs, pneumonia, feeding tube complications, falls, and seizures – many preventable with timely, on-site care. These unnecessary transfers not only distress vulnerable patients and families but also drive-up health care costs, contributing to $14.3 billion in annual Medicare spending.

A new international study led by Kaunas University of Technology reveals that digital mental health start-ups reaching unicorn status tend to secure private funding early, prioritise simple, scalable services, and use subscription models –  while reliance on state funding may actually hinder growth. The research, based on 125 ventures (including 12 unicorns), suggests success stems from strategic, complementary choices rather than technological complexity alone. Researchers call for a shift in European investment policy to focus more on market relevance and user impact rather than deep tech or rigid scientific criteria.

A new Virginia Tech study highlights the impact of marijuana legalization on hotels.

Digital twins for automated material handling systems (AMHSs) of semiconductor and display fabrication industries suffer from parameter uncertainty and discrepancy. This leads to inaccurate predictions, ultimately affecting performance. To address this, researchers have developed a new Bayesian calibration framework that simultaneously accounts for both parameter uncertainty and discrepancy, improving the prediction accuracy of digital twin models. This innovative framework holds great potential for enhancing digital twin applicability across diverse industries.