Reducing the clerking time for patients overnight

Quality Improvement Poster Download

Background & Problem

At Cheltenham General Hospital (CGH), the Emergency Department (ED) becomes a minor injuries unit overnight. This means that several patients that need admission under the medical team are referred in the evening, just as most of the medical doctor team are going home. This leads to a mismatch between patient numbers and workforce. Consequently, medical patients were waiting too long to be clerked. Improving waiting times will improve patient safety and satisfaction. This involves all doctor grades of the medical clerking team and all medical patients admitted to CGH (several hundred a month). We wanted to improve the ‘clerking manpower’ to reduce waiting times without spending any money.

Aim

We attempted to reduce the waiting times for patients to be clerked overnight by 25%, comparing September/October 2015 with September/October 2016.

Method

I mapped out the entire junior doctor job plan to establish who should be clerking at what time, interviewed several of them to establish the precise job role requirement, took a snapshot audit over a 4 day time span to establish the number of patients clerked per doctor role and then collated anonymous feedback to find out barriers to clerking. I then approached the IT department to extract a large amount of data from ‘Patient First’ software, before analysing this.

Results

I demonstrated that the later in the day medical patients are referred, the longer they wait to be clerked by a medical doctor. Using this data, I persuaded the ACUC consultants to implement the major ‘change idea’, which was to re-brand a ‘post-post take ward round’ doctor a ‘clerking doctor’ and amend their shift pattern from 9:00 – 17:00 to 11:00 – 19:00. Through rota modelling, this provides a 22% increase in ‘clerking manpower’, and at a more appropriate time of day.

After this change idea was implemented, I extracted time stamp data from the admission software (Patient First). I compared September/October 2015 with the same months in 2016 and results exceeded the study aim; there was a 35% reduction in evening waiting times and an average 25% reduction in waiting times across a whole 24-hour period.

Implications

This project demonstrates that careful rota planning, clear role assignment and optimising the available workforce can improve patient care and safety without cost to the Trust. This specific scenario (ED becoming a minor injury unit overnight) is an uncommon model in the UK, but the principles of knowing the role of each team member throughout the day are eminently exportable to other clinical teams. The use of hard data in this case was key to proving the clinical suspicion that patients were waiting longer later in the day, and persuading the team to introduce the key ‘change ideas’.