<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/4C4F7BB7-F6E5-4C3D-95CB-B3E0C4D2EC92" ns1:id="4C4F7BB7-F6E5-4C3D-95CB-B3E0C4D2EC92"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/65C32D7A-3459-4BF6-B8CA-D64E4ED466C8" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D9DE1C85-416D-4EBE-A13A-43789E427C2A" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D9DE1C85-416D-4EBE-A13A-43789E427C2A" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/BC398E56-6DE9-4784-A356-301C98DA4389" ns1:rel="FUND" ns1:start="2020-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">59670</ns2:identifier></ns2:identifiers><ns2:title>Community Management of COVID-19 in care &amp;amp; nursing homes</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Elderly patients, especially with co-morbidities, are particularly vulnerable to COVID-19, with reported mortality rates of 10-20% for those over 70 years. The pandemic is imposing a massive burden on NHS services. Hospital facilities and GP practices have become overloaded and dangerous places for vulnerable people, who are now discharged prematurely or never admitted into hospital. This increases the burden on Adult Social Care (ASC) providers. Telemedicine can help to bridge the gap between clinicians and vulnerable communities. However, it is very difficult for a doctor to make diagnostic decisions on a respiratory case with co-morbidities based on just a video interaction.

The Feebris mobile platform enables non-medics to conduct health check-ups and a clinical team to conduct &amp;quot;remote ward rounds&amp;quot; in care/nursing homes. The platforms has specialist respiratory tools, including a digital stethoscope and AI for detecting &amp;amp; interpreting respiratory disease markers. This project will develop an AI toolbox for COVID-19 that, integrated with the base platform, will provide care teams with decision-support to identify COVID-19 cases remotely and facilitate clinical management. It will include specialist tools for: automated triage; disease progression monitoring; and communication of health status with clinicians and family, plus a digital user training module/programme to allow deployment at scale.

Current remote monitoring solutions offer no decision support for carers, are not geared for complex respiratory conditions, and have no AI for advanced remote monitoring. We have deployed our base platform into care/nursing homes across London and with a national live-in care provider. This puts us in a unique position to capture essential data for the development of the COVID-19 AI and achieve fast development &amp;amp; impact.

The impact of the COVID-19 toolbox in care homes is to standardise observation gathering, making carers more confident in making triage decisions and better equipped to provide essential information to remote clinicians. The pandemic requires urgent action and long-term restructuring of healthcare as long-term lung damage is expected in survivors. In the longer term, the technology will strengthen community management of COVID-19 and associated chronic issues, alleviating NHS pressure and ensuring high quality, proactive and personalised care.</ns2:abstractText></ns2:project>