AI-powered real-time healthcare supplier profile and COVID-19 supply risk matrix

AI 驱动的实时医疗保健供应商概况和 COVID-19 供应风险矩阵

• 批准号: 90205
• 金额: $ 31.85万
• 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=90205
• 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 Moreover, to conduct supplier scanning exercise, the NHS and other buyers follow a manual and outdated process that only surfaces a fraction of global suppliers.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.

在我们应对新冠肺炎 (COVID-19) 大流行的过程中，对全球医疗保健供应链的影响持续加大，导致广泛的系统性不确定性。对于 NHS 等医院和卫生系统来说，由于资源紧张，大流行的需求冲击和整体供应短缺构成了巨大的挑战，需要实时的风险调整解决方案。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对于任何医疗保健买家（例如医院/信托机构/诊所）来说是最关键的任务。在 NHS 和其他医疗保健买家中，大部分预算花在一级大型供应商上，其余花在二级和三级供应商上（中低支出）。正是这种对一小部分一级供应商的过度依赖，使 NHS 面临高风险，因为这些供应商也在其他国家/地区开展业务，同时与其他医院开展业务，同时管理其有限时限的总量能力或供应能力。此外，为了进行供应商扫描，NHS 和其他买家遵循手动且过时的流程，仅显示全球供应商的一小部分。这是由于医疗保健系统内部和整个医疗系统内的 COVID-19 导致需求同时激增，导致全球供应链全面崩溃，导致个人防护装备、防护装备、设备和药品严重短缺的主要原因。 为了让 NHS 和其他医疗保健买家更好地应对新出现的 COVID-19 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来创建实时医疗保健供应商档案和产品/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 持续了解供应方动态，并将持续提供供应链不断发展状态的关键任务可见性，不仅关注现有瓶颈，还识别未来的潜在挑战。该项目将开发可在项目生命周期内被 NHS 使用的产品，以及那些可以在项目之外推广并在长期内使更广泛的医疗保健提供者受益的产品。