<?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="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/8F6A80D6-FD7E-4B4E-BC5A-AB594BC329E2" ns1:id="8F6A80D6-FD7E-4B4E-BC5A-AB594BC329E2"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/B9751CE1-3B4D-426A-A8A5-15019863079B" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/5E30637E-8A7E-42D1-94A7-EAC0C49BCE5C" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/362276FA-9E5A-44ED-B712-530B69176157" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/5E30637E-8A7E-42D1-94A7-EAC0C49BCE5C" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2018-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/CFC0908A-A91A-430C-A4D8-14F073339C23" ns1:rel="FUND" ns1:start="2018-02-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">133397</ns2:identifier></ns2:identifiers><ns2:title>Patient Automated Triage &amp;amp; Clinical Hub Scheduling (PATCHS)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>&amp;quot;Primary care is the foundation of the NHS, accounting for 90% of all NHS contacts; over 340m consultations per year. Over recent years it has come under significant strain due to increasing demand, a hiring/retention crisis, and budget constraints. Effective triage processes - efficiently and accurately directing patients to the appropriate services, be that a GP, alternative health professional or self-care -- can significantly ease pressures on GPs by reducing avoidable consultations; estimated at 27%. This could save the NHS over &amp;pound;700m per year\* while improving patient satisfaction, due to shorter waiting times and longer appointments. Unfortunately, current triage processes are inconsistent and often ineffective, relying on non-clinically trained staff such as GP receptionists.

This feasibility study will assess the opportunity and potential impact of applying an existing technology Artificial Intelligence (AI) triage in the primary care triage process. AI triage is well-suited to primary care due to the large amount of patient data, which allows the algorithm to identify both common more unusual ailments.

\* based upon NHS England estimates of &amp;pound;100k annual savings per practice for telephone triage.&amp;quot;</ns2:abstractText></ns2:project>