The project team believes that the platform will help to prevent future shortages of essential products in future, such as the shortage of PPE reported by many health and social care organisations during the first wave of the Covid-19 pandemic.
With the ability to analyse NHS and global procurement data from previous supply contracts, the platform will aim to allow NHS buyers to evaluate credibility and capability of suppliers to fulfil their order. Each supplier would have a real-time ‘risk rating’ with information on the goods and services they supply.
Researchers at Sheffield University's Information School are said to be developing Natural Language Processing (NLP) methods for the automated reading and extraction of data from large amounts of contract tender data held by the NHS and other European healthcare providers. Vamstar will work alongside them to incorporate the information into a healthcare procurement marketplace, accessible to NHS procurement teams.
Dr Ziqi Zhang, leader of the Sheffield team developing the NLP methods, explained that procurement and tender data is not currently readily available to NHS procurement teams ordering stock.
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“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 capability and credibility,” Zhang said.
“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 novel healthcare NLP models for this research project.”
It is hoped that the platform will make it easier for the NHS to respond quickly to the needs of staff and access a wider supplier market including expanded access to SMEs.
Dr Richard Freeman, CTO for Architecture and Data Science from Vamstar described the pandemic demand for essential supplies as a ‘monumental challenge’ for the NHS. He added that the use of NLP, deep learning, big data and machine learning on the company’s global marketplace data would mitigate the risk of future surges in demand.
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