News Release 

Scientists develop algorithm to help relieve pressure on the NHS

Queen Mary University of London

Research News

New research suggests an algorithm could be used to help optimise the sharing of healthcare resources during the Covid-19 pandemic, preventing NHS intensive care units (ICU) from becoming overwhelmed.

The study, led by Queen Mary University of London, proposes a load balancing method to transfer critical ICU patients across hospitals and optimally allocate new patients, which could help to reduce stress on health systems in the second wave and potential subsequent waves to come.

The research team, which included scientists from the University of Exeter and the University of Bristol, tested the algorithm using available data from both the UK's NHS and Spanish health system. They showed that this mathematical approach could help redistribute up to 1000 ICU patients that otherwise likely wouldn't receive the appropriate intensive care.

During the pandemic, demand for ICUs varies across a country, with some hospitals receiving substantial numbers of patients early on in an outbreak whilst others are unaffected. These differences in demand create an opportunity to balance the load of patient admissions across hospitals, by rerouting patients from areas of high demand to local hospitals that have spare capacity.

Rerouting and load balancing solutions have a long history in areas such as computer networks, where usually different tasks are assigned to different interconnected servers and the servers can communicate and transfer tasks in order to minimise the global processing time. In this study, the researchers adopted a similar approach to manage ICU resources in hospital networks, where the "load" to be allocated is the amount of ICU patients or ventilators, and the rerouting takes place across hospitals.

Using the algorithm the researchers showed that when ICU demand is uniform across the country it is possible to enable access for up to 1000 additional cases in the UK in a single step of the algorithm, without needing to increase capacity. In more realistic scenarios, where we see differences in demand across hospitals or regions, the scientists found their new method could balance about 600 beds per step in the Spanish system when sharing resources locally, and over 1300 using countrywide sharing, potentially saving a large percentage of these lives that would otherwise not have access to ICUs.

It is hoped this mathematical approach could also be used to help reduce demand when the epidemic begins to decline, allowing hospitals to return back to normal as efficiently as possible.

Dr Leon Danon, Senior Lecturer in Data Analytics at the University of Exeter, said: "The current Covid-19 pandemic has put many national health systems under significant pressure, particularly for ICUs and ventilators. So far balancing patient loads in times of high demand has occurred spontaneously, for example with hospitals sharing daily information on demand and availability of resources with colleagues in other local hospitals. Whilst this quick action can help in the immediate, once multiple hospital become overwhelmed the pattern of demand becomes more complex and a more systematic approach is needed. Our load sharing methodology can help to prevent health services becoming overwhelmed by the excessive demand for intensive care, which is particularly critical when the second wave we are experiencing can now be coupled with the flu season."

Dr Lucas Lacasa, Reader in Applied Mathematics at Queen Mary, said: "We have validated that the method works with realistic data from the UK and Spain, and shown it can be used to load balance patients in real time. We are currently in the process of exploring how to operationalise the method within the healthcare system, and are developing a user-friendly interface for the NHS, or other health systems across the globe, to be able to embed this technology within the set of measures each country is already deploying to manage the pandemic."

"The method is easily portable to other countries as well, and whilst this load sharing algorithm has primarily been developed for the current pandemic, there's no reason a similar approach couldn't be used to load balance other healthcare resources."

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Notes to editors

  • Research publication: 'A flexible method for optimising sharing of healthcare resources and demand in the context of the COVID-19 pandemic' Lucas Lacasa, Robert Challen, Ellen Brooks-Pollock, Leon Danon PLOS ONE.
  • For more information and a copy of the paper, please contact:

    Sophie McLachlan
    Faculty Communications Manager (Science & Engineering)
    Queen Mary University of London
    press@qmul.ac.uk
    Tel: 020 7882 3787

About Queen Mary

Queen Mary University of London is a research-intensive university that connects minds worldwide. A member of the prestigious Russell Group, we work across the humanities and social sciences, medicine and dentistry, and science and engineering, with inspirational teaching directly informed by our world-leading research. In the most recent Research Excellence Framework we were ranked 5th in the country for the proportion of research outputs that were world-leading or internationally excellent. We have over 25,000 students and offer more than 240 degree programmes. Our reputation for excellent teaching was rewarded with silver in the most recent Teaching Excellence Framework. Queen Mary has a proud and distinctive history built on four historic institutions stretching back to 1785 and beyond. Common to each of these institutions - the London Hospital Medical College, St Bartholomew's Medical College, Westfield College and Queen Mary College - was the vision to provide hope and opportunity for the less privileged or otherwise under-represented. Today, Queen Mary University of London remains true to that belief in opening the doors of opportunity for anyone with the potential to succeed and helping to build a future we can all be proud of.

About the University of Bristol

The University is ranked within the top 10 universities in the UK and top 50 in the world (QS World University Rankings 2020); it is also ranked among the top five institutions in the UK for its research, according to new analysis of the Research Excellence Framework (REF) 2014; and is the 4th most targeted university by top UK employers.

The University was founded in 1876 and was granted its Royal Charter in 1909. It was the first university in England to admit women on the same basis as men.

The University is a major force in the economic, social and cultural life of Bristol and the region, but is also a significant player on the world stage. It has over 16,000 undergraduates and nearly 6,000 postgraduate students from more than 100 countries, and its research links span the globe.

About the University of Exeter

The University of Exeter is a Russell Group university that combines world-class research with high levels of student satisfaction. Exeter has over 23,000 students and is in the top one per cent of universities worldwide. Exeter is also ranked 10th in the Guardian University Guide 2020 and 12th in The Times and The Sunday Times Good University Guide 2020. In the 2014 Research Excellence Framework (REF), the University ranked 16th nationally, with 98% of its research rated as being of international quality, while in 2017, Exeter was awarded a Gold rating in the Teaching Excellence Framework (TEF) assessment.

http://www.exeter.ac.uk

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