Vamstar leads the development of a ground-breaking real-time global AI-powered healthcare suppliers risk profile

Vamstar, the data science based global B2B healthcare marketplace, wins funding to create an AI-powered healthcare suppliers risk profile with the University of Sheffield

London, March 19th, 2021  -– Vamstar, the data science based global B2B healthcare marketplace, has won a competitive applied research funding from UK Research and Innovation, to develop a healthcare suppliers’ risk profile, reducing the chances of future shortages of critical products and services during times of national crises.

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.

The platform will give a real-time risk-rating to each supplier, including information about the goods they supply, the quality, and their history of working with the NHS and other EU hospitals. The project aims to diversify the supply base and reduce the overall risk of the NHS purchasing from companies who may be unable to fulfill an order and of receiving sub-standard goods.

The new project comes as the UK Government was recently criticised for rejecting claims that there was a national shortage of PPE during the first wave of the pandemic, despite many health and social care organisations having reported difficulty acquiring sufficient stocks of essential PPE to keep staff safe.

Over-reliance on a few healthcare suppliers and an increase in global demand, contributed to the heavy shortages of PPE, essential equipment and pharmaceuticals within the NHS throughout the beginning of the pandemic in the UK.

Dr Richard Freeman, CTO for Architecture and Data Science from Vamstar, said: “Using NLP, deep learning, big data and machine learning on our global marketplace data, with the NHS and EU contracting data will create a supplier risk profile that is easier and more efficient for the NHS to manage its supply chain, mitigating the risk of future surges in demand for essential products and services by spreading demand over a wider number of suppliers. For hospitals and health systems such as the NHS, the pandemic demand and the overall shortages of essential supplies represented a monumental challenge.”

“Going forward efficient supplier sourcing, supplier selection, and continuous supplier-risk assessment are the most critical tasks for any healthcare buyer. Through harnessing the technological advancements in artificial intelligence, deep learning and natural language processing will help us develop a platform to provide up to date, instant access to information about global healthcare suppliers previously only available through laborious manual research.”

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 benefit the wider range of healthcare providers.

Vamstar is working with scientists from the University of Sheffield who are developing novel Natural Language Processing (NLP) methods for the automated reading and extraction of data from large amounts of unstructured contract tender information and spend data held by the NHS and other European Healthcare providers.

Dr Ziqi Zhang will lead the team at the University of Sheffield developing the novel NLP methods: “Currently, procurement and tender data are stored in silos and various digitised documents, meaning this information isn’t readily available to NHS procurement teams for central assessment and analytics. Supplier selection during the procurement process is an extremely slow and laborious process for NHS buyers and involves manually locating, reading, and analysing a significant amount of such data from various sources in order to evaluate a supplier’s capacity and credibility. NLP involves a series of techniques for the automated analysis of a variety of documents, to enable the efficient retrieval and consolidation of relevant data for procurement and we will develop state-of-the-art healthcare-specific NLP models in this research project”

The platform will help the NHS access a wider market of suppliers and provide a risk rating to help procurement teams find a reliable selection of suppliers. In addition it will better prepare the NHS and other healthcare buyers for possible pandemic waves, post-COVID-19 recovery and improve procurement processes.

Vamstar is a data science powered global B2B healthcare marketplace platform. They aggregate $2 trillion of demand for healthcare products and services using machine learning and providing real-time insights to buyers and suppliers to accelerate transactions.

Vamstar’s enriched data on buyers, outcomes, and contracts (including tenders) reveal interdependencies across complex contracting markets. By seeing the big picture and all the connections, Vamstar provides healthcare stakeholders with valuable market insights and perspectives.

Vamstar partners with leaders in the industry, academia, and government in 70 countries to apply higher-level thinking to daily tasks and strategic issues. They offer their customers solutions to make them more efficient and help them make data-driven informed decisions to secure their future. For more information, visit https://vamstar.io