AI tool predicts hospital bed demand
An artificial intelligence (AI) tool developed by UCL and UCLH is being used to predict how many patients coming from A&E will need to be admitted to hospital.
Described in Nature Digital Medicine, the tool estimates how many hospital beds will be needed by looking at live data of patients who have arrived at the hospital’s emergency department.
In the study, the research team showed that the tool was more accurate than the conventional benchmark used by planners, based on the average number of beds needed on the same day of the week for the previous six weeks.
The tool, which also accounts for patients yet to arrive at hospital, provides more detailed information than the conventional method. Instead of a single figure prediction for the day overall, the tool includes a probability distribution for how many beds will be needed in four and eight hours’ time and provides its forecasts four times a day, which is emailed to hospital planners.
Researchers are now working with UCLH on refining the models so that they can estimate how many beds will be needed in different areas of the hospital, for example beds on medical wards or surgical wards.
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