Leads: Professor Peter Watkinson and Dr Sarah Vollam
Patients who have been discharged from intensive care units (ICUs) are at high risk. The amount of monitoring they receive is reduced on discharge from the ICU, and this is of concern to both patients and their families. In this sub-theme we aim to reduce poor outcomes and improve patient and family experience through use of wearables from ICU through to the home for earlier detection of unexpected deterioration in high-risk groups.
We are linking next-generation monitoring data with detailed in-ICU data (including vital signs and falls) and the hospital electronic patient record to build personalised machine-learning models for each patient as they move from intensive care to the general ward and into the community.
In collaboration with the Surgical Innovation Technology and Evaluation theme, we are then applying these strategies to other high-risk groups to improve outcomes after major surgery.