British tech firm Faculty partners with NHS to forecast A&E admissions
A new A&E demforecasting tool is being rolled out to 100 NHS acute trusts in Englto help tackle waiting list backlogs.
The tool, co-developed with British artificial intelligence (AI) firm Faculty, utilises modelling techniques machine learning technology to predict pressures from emergency demand. This allows frontline staff to make informed decisions on how to best plan.
Data sources on external factors, such as COVID-19, traffic, public holidays, have been incorporated to improve the model’s accuracy, there are aspirations to include other data sources such as weather in the future.
WHY IT MATTERS
The NHS is facing huge elective backlogs from the pandemic, with almost six million people in Englwaiting to start routine hospital treatment in November 2021.
It is intended for the A&E admissions forecasting tool to support allocation of staff resources, to help staff make decisions on when elective care delivery should be prioritised.
This includes knowing when to free up beds or work with partners in the wider health care system to ensure capacity for patients.
Admission forecasts are broken down by age, allowing staff to plan for specific bed needs, such as for paediatric patients or for elderly patients – as well as by NHS trust, allowing staff in regional national teams to spot areas with expected demsurges.
THE LARGER CONTEXT
At the start of the pandemic, Faculty worked with NHSX to help build a COVID-19 early warning system to forecast hospital admissions life-saving equipment up to three weeks in advance.
Faculty also supported NHSX as a partner for the NHS AI Lab, where it aided with the development of the National COVID-19 Chest Imaging Database (NCCID), was recently on the research group which created a blueprint for testing the robustness of AI models.
ON THE RECORD
Professor Chris Moran, national strategic incident director, NHS EnglNHS Improvement, said: “This leading technology has been developed to support hospitals by alerting them of potential upcoming surges in A&E admissions this will support decision-making flexible use of resources capacity, meaning the NHS will be in a better position to prepare for surges in demand.”
Professor Stephen Powis, NHS national medical director, said: “Pressures remain high, but staff are determined to address the COVID-19 backlogs that inevitably built up throughout the pandemic, while that cannot happen overnight, harnessing new technologies like the A&E forecasting tool to accurately predict activity levels free up staff, space resources will be key to helping deliver more vital tests, checks procedures for patients.”
Myles Kirby, director of health life sciences, Faculty, said: “By better forecasting patient demand, we are helping staff tackle treatment backlogs by showing them who is set to be admitted, what their needs are, which staff are needed to treat them.”