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AI-Driven Primary Care Clinical Assessment Platform for Allied Health Professionals (PC-CAP)

AI-Driven Primary Care Clinical Assessment Platform for Allied Health Professionals (PC-CAP)
面向联合医疗专业人员的人工智能驱动的初级保健临床评估平台 (PC-CAP)
批准号:
10038273
负责人:
金额:
$33.21万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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英文摘要
NHS Primary Care is in crisis: GP practices are experiencing sharply declining GP numbers (1,565 FTE fewer than 2015) and rising demand (6.1m waiting lists; 30.1m appointments in March 2022). They are struggling to recruit and retain staff (7,000 GP shortfall projected within 5 years). This impacts patient care.The NHS Long Term Plan aims to meet these challenges, allocating £4.5bn to expand the role of allied healthcare professionals (AHPs), giving more front-line clinical assessment and triage responsibilities to nurse associates, physician associates, clinical pharmacists and social prescribing link workers.This workforce redesign brings new challenges. AHPs are reporting feeling out-of-their-depth and often requiring senior guidance. This is resulting in inefficient, disrupted workflows, inconsistent patient delivery and delays in care, creating high levels of burnout (44% of AHPs reported job anxiety in 2020/21) and 20% turnover. AHPs have raised the urgent need for AHP-specific support tools, with existing systems not meeting their needs.This project will deliver DemDx's Primary Care Clinical Assessment Platform (PC-CAP): the only support tool designed specifically for and with AHPs. Innovations include:* Technical: AI allowing dynamic consideration of complex associations across 10,000s of symptoms, differentials and "red flags" in validated NICE CKS data. PC-CAP's data-driven (vs specialist-driven) approach will enable AHPs to make sense of complex data associations to make safe, consistent decisions. PC-CAP provides data weighting, enabling identification and prioritisation of most probable conditions, driving accuracy of recommendations. It links to local pathways/protocols to inform best referral options. All outputs are tailored to AHP competencies, and we initially focus on common minor illnesses. Proof-of-concept of the AI has been demonstrated at Moorfield's Eye Hospital.* Scientific: powered by datasets, including Oxford-RCGP dataset, covering 1800 general practices, NICE CKS, and PCN anonymised patient data.* Commercial: the only solution designed specifically for AHPs; fully interoperable system which can be licenced and integrated into clinical pathways worldwide..PC-CAP offers socio-economic impact by:* enabling AHPs to confidently, autonomously undertake appointments.* increasing GP capacity to focus on complex patients.* reducing waiting times, preventing escalation of conditions, enabling shorter treatment pathways, reducing hospital admissions; improving care and quality adjusted life years.* enabling £16.9m/year NHS savings: reduced operational (£6.8m), A&E visit (£5m), ambulance (£3.8m) and GP locum costs (£1m).Our serviceable addressable market is £160m UK and £2.3bn worldwide, with use cases in primary, community, urgent, emergency and secondary care.
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Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information