Leads: Professor Andrew Farmer and Professor Dan Lasserson
High quality, safe healthcare for acute conditions is increasingly being delivered in and out of hospital settings. Our aim for this programme of work is to optimise the role of remote monitoring in virtual wards and deliver evidence for the best use of these technologies.
To deliver this, we are building on our development of innovative acute medical care models and expertise in remote management of chronic disease, underpinned by wearable and non-contact vital sign and activity monitoring technologies.
Initially we are focusing on remote virtual ward monitoring for acutely ill people where there is already an extensive programme of work to develop capacity for this care. But the clinical pathways, use of remote monitoring technology, interpretation of data and collection of data for evaluation is evolving rapidly.
Work includes investigating current pathways for a range of acutely unwell people, including those with respiratory conditions and conditions associated with frailty; deploying wearable and non-contact technologies in the home for selected conditions across the local integrated care system before undertaking a multi-site evaluation; and training machine learning (ML) prediction algorithms to identify increased risk in our virtual-ward populations and to prioritise intervention.