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or ability-to-supply.Moreover, to conduct supplier scanning exercise, the NHS and other buyers follow a manual and outdated process that only surfaces a fraction of global suppliers.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.

当我们浏览COVID-19的大流行时，对全球医疗保健供应链的影响继续持续，导致了广泛的系统不确定性。对于医院和卫生系统（例如NHS），具有伸展的资源，大流行需求冲击和整体供应短缺代表了需要实时风险调整的解决方案的巨大挑战。这意味着有效的供应商采购，供应商选择和持续的供应商风险评估是任何医疗保健购买者的最关键任务-1个大型供应商仍在用于2级和3级供应商（中等至低支出）上。正是这种过度依赖于一小部分级别供应商，使NHS暴露于高风险，因为这些供应商也在其他国家 /地区都有，并同时与其他医院开展业务，同时管理其有限的时间限制汇总除了进行供应商扫描练习，NHS和其他买家遵循手动且过时的过程，仅影响出一小部分全球供应商。这是从内部和整个医疗保健系统中与Covid-19引起的同时需求的主要原因，这导致全球供应链的完全崩溃，从而导致PPE，防护装备，设备和药品的大量短缺为了更好地为NHS和其他医疗保健购买者准备新兴的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的医疗保健供应商概况和产品/服务Level供应商的预测，由较早的研究赠款中开发的COVID-19基于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，并将连续地为供应链不断发展的状态提供关键的可见性，而不仅仅是关注现有的瓶颈，还要确定未来的潜在挑战。该项目将开发NHS在项目生命周期期间已经可以使用的产品，以及那些可以从项目中概括并在长期内受益于更广泛的医疗保健提供者的产品。