Friday, 07 May 2021
The University of Nottingham is part of a consortium of experts that have won funding to develop the world’s largest healthcare supply chain network system.
The experts will use artificial intelligence (AI), big data, deep learning and Natural Language Processing (NLP) to present a virtually real-time procurement picture to users.
Funded by Innovate UK, academics from the University of Nottingham are working with the University of Sheffield, led by Vamstar, a data science based global business-to-business healthcare and life sciences marketplace platform.
The network will connect buyers and suppliers across the healthcare and life sciences industries, allowing them to see the products, services and devices that are available around the world.
The current approach to supplier selection, management, and the overall procurement process in the health sector is a dated and complex manual process, leading to incoherent supply-demand matching and poor supply chain visibility.
In 2019, 44% of healthcare contracts within the European Union received just one applicant, and 15% had no bidders at all, costing the taxpayer billions in wasted critical healthcare resources, based on Vamstar’s analysis and EU commission data.
The Covid-19 pandemic is a recent example of how, when there is a surge in global demand for critical supplies, the apparent flaws and inefficiencies of the current healthcare marketplace are accentuated and expose the buyers to significant supply risk, such as unfulfilled orders or long supply delays because of increased demand.
The system will allow users to filter their search to narrow down their selection and will provide information on each supplier such as; its history with other buyers; stock levels; relationships with other organisations e.g. if they are a subsidiary; financial information from companies house; and whether they are a local supplier.
Dr Aris Georgopoulos, of the University of Nottingham, is leading a team of public procurement experts on the project.
This system will completely revolutionise healthcare procurement and will essentially act as a match-maker between buyers and suppliers. The procurement process will become more efficient and will give users a full picture of the market at that time, allowing them to make informed choices based on the latest data.
Dr Georgopoulos added: “Transparency has been one of the main characteristics of modern public procurement regulation and policy. However, transparency of information does not always lead to “visibility of information” as indicated by our recent research. This lack of visibility is even more prevalent in the connections between the various entities in the healthcare supply chain networks.
"Due to the scale of the relevant data and the complexity of relationships/connections, the challenge for increased visibility can only be solved using technological solutions, based on Artificial Intelligence (AI), Deep Learning, Natural Language Processing (NLP) and big data analysis which can function as efficiency multipliers assisting public buyers to achieve better and more sustainable outcomes.”
At Vamstar, we are representing a healthcare and life sciences marketplace using networks as it allows us to capture the richness of all relationships, to infer metrics such as the strength of connectivity or weaknesses in a supply chain, as well as derive new relationships due the nature and plasticity of the network topology itself.
Dr Ziqi Zhang, Lecturer and expert in NLP and Text Mining, University of Sheffield said: “NLP involves a series of techniques for the automated analysis of a very large amount of documents, to enable the efficient retrieval and consolidation of relevant data for the healthcare supply chain. It will allow the extraction of supply chain data points representing hospitals, suppliers, and products and services, and the connection of these data points based on complex relationships mined from various data sources such as tender and contracts.”
The experts believe that there is a critical need for an e-marketplace in healthcare that focuses on:
- Improving visibility of supply/demand data that are currently heterogeneous or inaccessible
- Giving access to all suppliers and buyers, allowing capturing of the “long tail” of SMEs in the procurement mix
- Allowing effective and efficient supply chain management to enable connected performance tracking and measurement of the procurement relationships
- Allowing a lens to gauge the market to inform policy making for the new industrial landscape.
More information is available from Dr Aris Georgopoulos in the Faculty of Social Sciences at the University of Nottingham at Aris.Georgopoulos@nottingham.ac.uk; or Katie Andrews, in the Press Office at the University of Nottingham at Katie.Andrews@nottingham.ac.uk
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Notes to editors:
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