NHS Digital has announced a new trial to use machine learning techniques to plan and manage COVID-19 treatment resources.
The system developed by NHS Digital and University of Cambridge is to help predict the upcoming demand for intensive care (ICU) beds and ventilators needed to treat patients with COVID-19 at individual hospitals and across regions in England.
The system called, The COVID 19 Capacity Planning and Analysis System (CPAS), uses data from Public Health England with machine learning techniques developed by data scientists to help support planning and resource management.
Four hospitals this week are participating in the pilot to demonstrate its accuracy and support any changes before being rolled-out further.
Professor Jonathan Benger, Chief Medical Officer, NHS Digital “With the pressure being placed on intensive care by the current coronavirus pandemic it is essential to be able to predict demand for critical care beds, equipment and staff.”
“CPAS allows individual hospitals to plan ahead, ensuring they can give the best care to every patient. At the same time, the wider NHS can ensure that the ventilators, other equipment and drugs that each intensive care unit will need are in place at exactly the time they are required.”
“In the longer term, it is hoped that CPAS can be used to predict hospital length of hospital stay, discharge planning and wider intensive care demand in the time that will come after the pandemic.”
NHS Digital said the system will help hospitals predict how many patient may require admission to ICU, how many may require ventilators, and how long patients are likely to be in hospital or ICU.
CPAS is built around a machine learning engine called Cambridge Adjutorium, developed by Professor Mihaela van der Schaar and her team at the University of Cambridge. Cambridge Adjutorium has already been used to develop insights into cardiovascular disease and cystic fibrosis.
Dr Jem Rashbass, Executive Director for Master Registries and Data at NHS Digital “Professor Van Der Schaar is an engineer, and she leads a multidisciplinary team that develops, tests and delivers working new solutions to the really hard problems in medicine.”
“Two weeks ago, the team shared a method with the world that showed it was possible to do capacity planning for COVID-19 patients. We recognised that there was an opportunity to industrialise the methods and deploy this as a service through the national infrastructure managed by NHSD and deliver a real data-driven planning tool to hospitals.”
“Although the system uses data from individuals to build its models, the system does not make treatment decisions about individual patients. Rather, by aggregating that data we can make more accurate predictions about larger groups, at the level of a hospital, a trust, a region or nationally. So while we can say with a high level of confidence that 30 out of 40 ITU beds in a hospital will be occupied next week, we are not trying to predict which patients will be in them.”
The tool also includes a “simulation environment” which will allow planners to test the effect of alternative scenarios, such as increasing the number of available beds or changes in the profile of patients admitted.
