AI-powered real-time healthcare supplier profile and COVID-19 supply risk matrix (Resilience Fund)

AI 驱动的实时医疗保健供应商概况和 COVID-19 供应风险矩阵（弹性基金）

• 批准号: 10024605
• 金额: $ 8.34万
• 依托单位: VAMSTAR LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10024605
• 关键词: AI; powered; real; time; healthcare

As we navigate through the COVID-19 pandemic, the impact on global healthcare supply chains continues to mount, leading to widespread systematic uncertainty. For hospitals and health systems such as the NHS, with stretched out resources, the pandemic demand shock and the overall supply shortages represents a monumental challenge that needs real-time risk-adjusted solutions. This means efficient supplier sourcing, supplier selection, and continuous supplier-risk assessment are the most critical tasks for any healthcare buyer, such as hospitals/trusts/clinics.Within the NHS and other healthcare buyers, the majority of this budget is spent on tier-1 large suppliers with remaining being spent on tier-2 and tier-3 suppliers (medium to low spend). It is this over-reliance on a small set of tier-1 suppliers that exposes the NHS to high risks, as these suppliers are also present in other countries and do business at the same time with other hospitals while managing their limited time-bound aggregate capacity or ability-to-supply.Moreover, to conduct supplier scanning exercise, the NHS and other buyers follow a manual and outdated process that only surfaces a fraction of global suppliers. This is the primary reason that a concurrent spike in demand due to COVID-19 from within and across the healthcare systems, that led to a total collapse of the global supply chain, leading to heavy shortages for PPE, protective gear, equipment, and pharmaceuticals.To better prepare the NHS and other healthcare buyers for the emerging COVID-19 wave and to prevent widespread shortages, Vamstar will leverage cutting-edge big data, deep learning and artificial Intelligence to create a real-time healthcare supplier profile and product/service level supplier forecasts, powered by the COVID-19 risk-based framework developed in an earlier research grant. This will help the NHS to maintain an ongoing view of the supply-side dynamics and will provide mission critical visibility into the evolving state of the supply chain on a continuous basis,not just focusing on existing bottlenecks, but also identifying future potential challenges. The project will develop products that can already be used by the NHS during the project lifecycle, but also those that can generalise beyond the project and benefit the wider range of healthcare providers in the longer term.

随着COVID-19疫情的蔓延，全球医疗供应链受到的影响持续增加，导致广泛的系统性不确定性。对于医院和NHS等卫生系统而言，由于资源紧张，大流行的需求冲击和整体供应短缺是一个巨大的挑战，需要实时调整风险的解决方案。这意味着高效的供应商采购、供应商选择和持续的供应商风险评估是任何医疗保健买家（如医院/信托/诊所）最关键的任务。在NHS和其他医疗保健买家中，此预算的大部分用于一级大型供应商，其余用于二级和三级供应商（中等至低支出）。过度依赖一小部分一级供应商，使NHS面临高风险，因为这些供应商也存在于其他国家，同时与其他医院开展业务，同时管理其有限的有时限的总产能或供应能力。此外，为了进行供应商扫描，NHS和其他买家遵循的是一种过时的手工流程，只有一小部分全球供应商才能看到。这是由于新冠肺炎导致医疗系统内部和整个医疗系统的需求同时激增，导致全球供应链全面崩溃，导致PPE，防护装备，设备和药品严重短缺的主要原因。为了更好地为NHS和其他医疗保健买家做好准备，以应对新冠肺炎浪潮，并防止广泛的短缺，Vamstar将利用尖端的大数据，深度学习和人工智能，以创建实时医疗保健供应商概况和产品/服务水平供应商预测，由早期研究资助中开发的基于COVID-19风险的框架提供支持。这将有助于NHS保持对供应方动态的持续看法，并将在持续的基础上提供对供应链演变状态的使命关键可见性，不仅关注现有的瓶颈，而且还确定未来的潜在挑战。该项目将开发NHS在项目生命周期内已经可以使用的产品，以及那些可以推广到项目之外并从长远来看使更广泛的医疗保健提供者受益的产品。