R&D for a Virtual Ward Sensing Device for High-Risk Chronic Patients

WarnerPatch是一种非侵入性远程监护(虚拟病房)的医疗设备。它使用一种专门设计的传感方法和开发的AI算法来测量组织健康以预测疾病的恶化。在医院或家里使用时，早期退化症状被识别出来，因此临床医生可以提供预防性护理，以改善患者结局并降低护理成本。我们专注于糖尿病和血管疾病(即外周血管疾病(PVD))，这些疾病可能是心脏病发作、中风、全身感染、溃疡或坏疽的结果或原因，可能导致截肢和死亡。全球有2亿人面临发展为这种疾病的风险，占欧盟27国的1300万人，略高于美国和英国的500万人。每年有60万名患者被截肢，其中50%的死亡率在截肢后两年内，30%的不必要截肢是由于认识到疾病的恶化。在疫情大流行和长新冠肺炎综合征期间，需要紧急医院护理的患者数量增加了60%，大大超出了现有的剩余资源。最小可行产品的开发使用其人工智能算法完成，并在模拟环境中进行测试/验证。该项目的目标是完成法规要求下的物理产品的研发，同时提高产品的可制造性，包括非关键部件的回收/翻新过程。在项目结束时，我们将能够启动商业活动的认证程序。我们将继续与利兹-教学-医院-国民保健服务信托基金(LTHT)和NHS-Arden-and-Greater-East-Midlands-Commissioning-Support-Unit(AGEM)合作，开发更详细的数据包，包括健康经济学(预算-影响和成本效益)。使用我们的设备将改善患者结果，同时通过以下方式降低医疗成本：1.快速识别有生命危险的患者，及早治疗患者，阻止疾病恶化：减少医院重症监护室和急诊室入院/就诊次数。帮助临床医生对患者进行分层，以便更密切地监测。通过持续的远程监测，协助脆弱和高危患者与社会保持距离。协助低风险患者安全及早出院，同时远程监测他们的情况；减少卧床天数和工作人员负担，并腾出临床设施的容量。

WarnerPatch is a medical device for non-invasive remote monitoring (virtual ward). It measures tissue health to predict disease worsening using a specifically designed sensing method and developed AI-algorithm. While being used at the hospital or at home, early degrading symptoms are identified so clinicians can give preventive care to improve patient outcomes and reduce care costs.We are focusing on diabetes and vascular diseases (i.e. peripheral vascular disease (PVD)), which can be the result of, or cause, heart attack, stroke, general infection, ulceration or gangrene, potentially leading to amputation and death.Worldwide, 200M people are at risk of developing this condition accounting for 13M in EU27, slightly more in the USA and 5M in the UK. Amputation is performed on 600K patients a year, with 50% death rate within two years after amputation and 30% of unnecessary amputation due to late recognition of disease-worsening.During the pandemic and with the long COVID-19 syndrome, the number of patients requiring emergency hospital care has increased by 60%, significantly stretching the current remaining resources.The minimum viable product development was finalised with its AI-algorithm and tested/validated in a simulated environment.The goal of this project is to finalise the R&D of the physical product under regulatory requirement while improving the product manufacturability including recycling/refurbishment processes of non-critical parts. At the end of the project, we will be able to start the certification processes for commercial activities. We will continue working with the Leeds-Teaching-Hospital-NHS-Trust (LTHT) and NHS-Arden-and-Greater-East-Midlands-Commissioning-Support-Unit (AGEM) for a more detailed data-pack development with health-economics (budget-impact and cost-effectiveness).Using our device will improve patient outcomes while reducing care costs by:1. Quickly identifying patients at risk of developing life threatening conditions, to treat patients earlier and stop the illness from worsening: reducing hospital ICU and A&E admission/visits.2. Helping clinicians stratifying patients for closer monitoring.3. Assisting in social distancing of fragile and high-risk patients with continuous remote monitoring.4. Assisting in the safe early discharge of low-risk patients whilst monitoring their condition status remotely; reducing bed-days and staff burden, and, freeing-up capacity in clinical facilities.