Overcrowding and trolley waits in Emergency Departments occur when there are insufficient beds available in the hospital for patients who need to be admitted from the Emergency Department. Patients often wait prolonged periods for a bed. Overcrowding has been shown to result in worse outcomes for patients. These worse outcomes apply to both patients who wait on trolleys for beds, and to other patients who attend the Emergency Department for treatment during periods of overcrowding.
Overcrowding occurs when demand for beds exceeds the number of beds available. If bed demand could be predicted on a hourly basis it would be easier to match supply with demand, and overcrowding could be reduced.
This project will look at patient attendances and admission over a 14 month period. All patients who are admitted from the Emergency Department during that period will be included and information about day, date and time of attendance will be collected. The collected data will be analyzed. Using the results of this data analysis I will investigate if it is possible, based on patient numbers earlier in the day, to predict the level of demand for beds later in the day. If significant patterns exist, and they can be identified, they will be very useful in the day to day management of beds in the hospital.
I will use this information to develop a model which can be used to predict bed requirements throughout the day and week. This model could be used to predict and prevent overcrowding.
