An AI-enabled multimorbidity care service

基于人工智能的多病种护理服务

• 批准号: 10099910
• 金额: $ 44.14万
• 依托单位: APPT-HEALTH LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10099910
• 关键词: AI; enabled; multimorbidity; care; service

Providing preventive and proactive primary care for patients with multiple long-term conditions (multimorbidity) is a major challenge facing the NHS. The Major Conditions Strategy identified that 25% of the population are diagnosed two-or-more of the six chronic and long-term conditions that account for over 60% of ill-health and early death in England (Department for Health and Social Care, 2023). With an ageing population and improving survival rates, the number of patients living with multimorbidity is rapidly increasing, putting significant pressure on limited NHS resources.GP practices and Primary Care Networks (PCNs) are accustomed to planning care delivery around treating a person based on an individual health condition. The gold-standard of care involves 'Care Coordinators' managing complex cases, but due to workforce pressures and heavy workloads, they struggle to manage multiple, separate patient lists and engage patients in preventive self-care. Several confounding systemic factors make it difficult to deliver high-quality multimorbidity care :* Market failure - unclear accountability and free-rider effects* Two-sided problems - public uptake must match health service capacity* Broken incentives -rewarding single-condition outputs not outcomes* Urgency bias - prioritising urgent task over important onesThis paradigm isdisastrous for patients, who feel overwhelmed navigating the system and receive conflicting advice and hard-to-follow treatment regimens, negatively impacting motivation, engagement, and outcomes.Effective multimorbidity care requires a patient-centred approach, focused on prevention and patient empowerment.Appt is a health technology SME thathas partnered with Network 6, a forward-thinking PCN in East London, to develop a radical new, AI-enabled multimorbidity care service. This approach focuses on using advanced machine learning techniques to understand the holistic need of each patient and map that need to the most suitable care plan (a sequence of appointments with different clinicians) which will ensure early diagnosis, self-management, and high-quality treatment that manages the complexity of their multimorbidity.

为具有多种长期疾病（多种多发性）患者提供预防和主动的初级保健是NHS面临的主要挑战。主要条件策略确定，在六种慢性和长期疾病中，有25％的人口被诊断为占不良健康和早期死亡的60％以上的二或长期状况（健康与社会护理部，2023年）。随着人口老龄化并提高了存活率，多种多发病的患者数量正在迅速增加，对有限的NHS资源施加了巨大压力。GP实践和初级保健网络（PCN）习惯于根据个人健康状况计划围绕某人进行护理服务。护理的黄金标准涉及“护理协调员”管理复杂案件的“护理协调员”，但由于劳动力压力和繁重的工作量，他们难以管理多个，单独的患者名单并让患者参与预防性自我保健。 Several confounding systemic factors make it difficult to deliver high-quality multimorbidity care :* Market failure - unclear accountability and free-rider effects* Two-sided problems - public uptake must match health service capacity* Broken incentives -rewarding single-condition outputs not outcomes* Urgency bias - prioritising urgent task over important onesThis paradigm isdisastrous for patients, who feel overwhelmed navigating the system and receive conflicting advice and难以遵循的治疗方案，对动机，参与和成果产生负面影响。有效的多发生率护理需要一种以患者为中心的方法，专注于预防和赋予患者的能力。Appt是一种健康技术中小企业，该中小型企业与Network 6与East London的Network 6合作，在East London的PCN上进行了一种新的新型PCN，才能开发出一种充满激光的新型，增强的多重疗法服务。这种方法着重于使用先进的机器学习技术来了解每位患者的整体需求，并将其映射到最合适的护理计划（与不同临床医生的任命序列），这将确保早期诊断，自我管理和高质量的治疗，以管理其多发性多发性的复杂性。