MonitorABLE - AI based Remote Patient Deterioration Detection Platform

MonitorABLE - 基于人工智能的远程患者病情恶化检测平台

• 批准号: 10072841
• 金额: $ 44.41万
• 依托单位: ABTRACE LIMITED
• 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
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10072841
• 关键词: MonitorABLE; AI; based; Remote; Patient

The **NHS and health systems around the world are under great pressure** with rising A&E attendances and hospital admissions alongside **budgetary pressures,** backlogs and an increasingly **ageing, less healthy population**.Hospitals are overflowing. However, **1 out of 5** emergency admissions are **avoidable** and responsible for taking up 13% of all NHS hospital beds, costing **£2.5 billion each year** with **40% of all deaths** having **preventable** causes.Given the current stresses on the healthcare budget and wider economy, increasing staff cannot be the only solution - **the equivalent of 8800 full-time GPs and 6400 Nurse posts will be vacant by 2030**. In this context, digital solutions are recognised to be essential by NHS England's Long-term Plan.**GP surgeries are responsible for monitoring patients**, reviewing them once or more each year if they have certain risk factors. However, in between these appointments, patients often have **subtle, gradual, often unrecognised worsening** over weeks or months before becoming unwell enough to require urgent care. A **wearable device could have picked up these signals** early, allowing assessment, treatment and avoiding deterioration.Remote Monitoring data, processed through machine learning based technology data creates an opportunity to build **an early-detection system for** patients who are at home with silent signals of **worsening health**. This project would allow **better targeting of _existing_ prevention and monitoring** activities and uses existing clinical capacity more effectively and efficiently, **enabling health systems _prevent_ hospitalisations,** patient harm whilst reducing health spending.**Wearable and remote monitoring devices are increasingly commonly used by patients including smartwatches (15%), fitness trackers (21%), and smartphones with step counters (90%)**. Furthermore, 6 out of 10 patients would agree to share this data with their doctor. All relevant information about a patient's health condition and their planned appointments will be in electronic health records (EHRs).This project will deliver a system which **combines data currently available to the GP** with additional **data collected from patients at home** using existing devices they might already have to.The system will identify and prioritise patients, suggesting modifications to their routine monitoring schedule allowing the GP to react early which a patient is suspected to be deteriorating by bringing them in for a more urgent appointment. The overall number of annual appointments is expected to be the same, but patients will be brought in at the right time for them, guided by rich data sources and advanced data processing techniques.

世界各地的 **NHS和卫生系统都面临着巨大的压力 **，A&E就诊人数和住院人数不断增加，加上 ** 预算压力，** 积压和日益 ** 老龄化，健康状况不佳的人口 **。医院人满为患。然而，** 五分之一 ** 的急诊入院是 ** 可以避免的 **，占所有NHS医院床位的13%，每年花费 ** 25亿英镑 **，**40%的死亡 ** 有 ** 可预防的 ** 原因。鉴于目前对医疗预算和更广泛的经济的压力，增加工作人员不是唯一的解决办法- ** 到2030年，将有相当于8800名全职全科医生和6400名护士职位空缺 **。在这种情况下，数字解决方案被认为是NHS英格兰长期计划的关键。全科医生手术负责监测患者 **，如果他们有某些风险因素，每年审查一次或多次。然而，在这些预约之间，患者通常会在数周或数月内出现 ** 微妙的，渐进的，通常无法识别的恶化 **，然后才变得不适，需要紧急护理。一个可穿戴设备可以在早期接收到这些信号，从而进行评估、治疗和避免恶化。通过基于机器学习的技术数据处理的远程监控数据为那些在家的病人建立一个早期检测系统创造了一个机会，这些病人的健康状况正在恶化。该项目将使 ** 现有预防和监测 ** 活动更有针对性，并更有效和高效地利用现有临床能力，** 使卫生系统能够预防住院治疗，** 在减少卫生支出的同时对患者造成伤害。患者越来越普遍地使用可穿戴和远程监控设备，包括智能手表（15%）、健身追踪器（21%）和带步数计数器的智能手机（90%）**。此外，10名患者中有6名同意与医生分享这些数据。所有关于病人健康状况和预约的相关信息都将记录在电子健康记录中。该项目将提供一个系统，该系统将 ** 全科医生目前可用的数据 ** 与使用现有设备从病人家中收集的额外数据 ** 结合起来。该系统将识别和优先考虑病人，建议修改他们的常规监测时间表，允许GP通过将他们带到更紧急的预约中来对怀疑患者恶化的早期反应。预计年度预约的总体数量将保持不变，但患者将在丰富的数据源和先进的数据处理技术的指导下，在合适的时间被引入。