John Bancroft

Purpose. This paper examines England’s Accident and Emergency (A&E) arm of the National Health Service (NHS). It considers the positive impact that Lean has had and Six-Sigma can have in A&E departments to improve the quality and reliability of the service offered, in an area that is facing performance challenges. Design/methodology/approach. Independent variables average monthly temperature data (degrees Celsius) obtained from the Met Office and weekly A&E data, patient volume is analysed alongside the dependent variable, the percentage of patients seen in four hours or less. Findings. The model produced a robust positive impact when Lean Six-Sigma is adopted, increasing the likelihood of A&E dependents meeting their performance objective to see and treat patients in four hours or less. Research limitations/implications. Further variables such as staffing levels, A&E admission type should be considered in future studies. Additionally, it would add further clarity to analyse hospitals and trusts individually, to gauge which are struggling. Practical implications. Should the NHS further its understanding and adoption of Lean Six-Sigma, it is believed this could have significant improvements in productivity, patient care and cost reduction. Social implications. Productivity improvements will allow the NHS to do more with an equal amount of funding, therefore improving capacity and patient care. Originality/value. Through observing A&E and its ability to treat patients in a timely fashion it is clear the NHS is struggling to meet it is performance objectives, the recommendation of Six-Sigma in A&E should improve the
reliability and quality of care offered to patients. 

Purpose. The purpose of this paper is to investigate England’s Accident and Emergency (A&E)
portion of the National Health Service (NHS). This paper is based upon weekly published data from A&E trusts across England, spanning from November 2010 to December 2014.
Design/methodology/approach – Emphasis is placed on a number of variables; month (time of
year), performance (patients seen in less than four hours), patient volume and exploring the
relationship between these variables. A deductive approach has been selected as the most appropriate for this paper and the format of a correlational study. Lean will be discussed as a philosophy throughout this paper, as a means to improve the NHS.
Findings. The NHS’s success in reaching its 95 per cent performance objective has in a gradual
downwards trend since the data started being published and the volume of patients seen in A&E is trending upwards. However, there is only a weak relationship between these variables, suggesting that peak in demand are effectively foretasted by the NHS and appropriate resources deployed to combat this. Additionally, there is a clear relationship between the time of year (month) and volume.
Research limitations/implications. The data used are not broken down and are aggregated from
A&E departments across the NHS in England. Therefore, outliers could be present that impact the data and results. Should outliers exist, these should be targeted for improvement or to be learnt from, depending on their ranking.
Practical implications. Should the NHS continue with their Lean transformation, it is believed that
efficiency will improvement throughout the organisation.
Social implications. Through the identification of volume trends better care and efficiency can be
provided to patients visiting the A&E departments of the NHS.
Originality/value. This paper analyses data over the past four years which can be used to spot past trends and predict future trends, therefore smoothing the reliability and quality of the care offered to patients. This can be achieved through a Lean transformation and a flexible resourcing approach.