Objectives & Background The Royal College of Emergency Medicine (RCEM) recent campaign, focusing on Emergency Department (ED) performance against the 4 hour standard, has highlighted exit block as a fundamental inhibitor of compliance with the standard. This leads to overcrowding, inefficiency processing patients, poor departmental flow and subsequent increased clinical risk. The study took place in the ED at St George's Hospital, London which is a major trauma centre seeing around 400 patients per day with the aim of quantifying the effect of exit block on the 4 hour standard.
Methods Data was extracted from our patient tracking system (Cerner iCLIP) on a daily basis for a period of 9 months commencing September 2014. Exit block was defined as patients occupying cubicles whilst awaiting a bed allocation for 6 hours or more. We only included adult patients in this study. The data for a given day was extracted the following morning. The cumulative duration of stay of all the included patients was divided by 24 to calculate the number of cubicles “lost” to exit block in that 24 hour period.
A scatter plot was then constructed of cubicles “lost” vs number of breeches of the 4 hour standard that day A correlation co-efficient was then derived. We also produce a similar graph for the same time frame correlating attendance number per day with number of breeches.
Results The data produced a correlation of 0.886 between cubicle loss and number of breeches per day. The correlation between attendance numbers and breeches was 0.208.
Conclusion From this data we have been able to quantify the effect of exit block on departmental performance. The correlation is 0.883. This supports the previous published work on the subject of exit block and the Royal College of Emergency Medicine's “STEP” campaign; specifically the “E” for exit block as something that needs urgent attention to improve 4 hour standard compliance. This data could be used to derive a performance prediction model based not only exit block as we have defined it but other variables., at play in the ED such as ambulance arrivals, age profile of patients, absolute number of patients etc⇓⇓.
- emergency departments
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