Hospitals will be able to predict daily A&E admissions weeks in advance using artificial intelligence software that analyses data including 111 calls and the weather.
It is being introduced in 100 NHS hospital trusts today after trials showed it had an “impressive” ability to forecast daily admissions, broken down by age, up to three weeks in advance.
It looks at factors including local Covid-19 infection rates, traffic and 111 calls to model how many patients are likely to turn up at a particular A&E department each day.
The software also takes into account public holidays such as New Year’s Eve, when A&E is frequently filled with injured or drunken partygoers.
NHS bosses told The Times that giving hospitals a daily forecast of expected admissions would help to speed up efforts to bring down record waiting lists of 6.1 million people.
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On days that are predicted to be quiet, managers will be encouraged to free up A&E staff to prioritise elective care and deliver more routine tests and operations to tackle the backlog.
If one hospital is forecast to have a particularly quiet day, it could “lend” staff to a neighbouring trust with high predicted admissions that day.
Hospital managers will also be able to increase bed capacity or the number of staff on call if they are forecast to have particularly high 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, and while that cannot happen overnight, harnessing new technologies like the A&E forecasting tool to accurately predict activity levels and free up staff, space and resources will be key to helping deliver more vital tests, checks and procedures for patients.”
A letter announcing the introduction of the “A&E admissions forecasting tool”, co-developed by the NHS with Faculty, an AI company, is being sent to trusts today. It says that “sophisticated modelling techniques” will support “planning for non-elective and elective activity”.
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Hospital managers “can use the forecasts alongside local information to determine whether additional bed capacity should be opened”, it adds, as well as determining whether elective care such as routine hip operations can go ahead.
Breaking down admission forecasts by age allows staff to plan for specific bed needs, such as for paediatric patients or for elderly patients.
The letter says that experts are working to expand the tool to include “weather data as a leading indicator”. Severe spells of weather are an important factor in A&E admissions.
The technology has been tested in nine NHS trusts. It was used during the pandemic to help to predict how many beds, ventilators and frontline staff hospitals would need each day.
Myles Kirby, director of health and life sciences at 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, and which staff are needed to treat them.
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“As this pilot shows, artificial intelligence is a force for good, and we’ll be working closely with the NHS to make sure the benefits are felt by patients and staff in all the hospitals chosen.”
