AI predicts demand for hospital beds coming from A&E

(Image: Pixabay CC0) An artificial intelligence tool developed by researchers at UCL alongside staff at UCLH is being used to predict how many patients coming through the emergency department will need to be admitted into the hospital, helping planners manage demand on beds. The tool, described in a new paper in Nature Digital Medicine , estimates how many hospital beds will be needed in four and eight hours' time 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, also provides much 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 fourand eight-hours' time and provides its forecasts four times a day, emailed to hospital planners. The research team is 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 (e.g. beds on medical wards or surgical wards).