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Accident and emergency (A&E) departments experience a secondary peak in patient length of stay (LoS) at around four hours, caused by the coping strategies used to meet the operational standards imposed by government. The aim of this paper is to build a discrete‐event simulation model that captures the coping strategies and more accurately reflects the processes that occur within an A&E department.

A discrete‐event simulation (DES) model was used to capture the A&E process at a UK hospital and record the LoS for each patient. Input data on 4,150 arrivals over three one‐week periods and staffing levels was obtained from hospital records, while output data were compared with the corresponding records. Expert opinion was used to generate the pathways and model the decision‐making processes.

The authors were able to replicate accurately the LoS distribution for the hospital. The model was then applied to a second configuration that had been trialled there; again, the results also reflected the experiences of the hospital.

This demonstrates that the coping strategies, such as re‐prioritising patients based on current length of time in the department, employed in A&E departments have an impact on LoS of patients and therefore need to be considered when building predictive models if confidence in the results is to be justified.

As far as the authors are aware this is the first time that these coping strategies have been included within a simulation model, and therefore the first time that the peak around the four hours has been analysed so accurately using a model.

This study seeks to examine the extent to which mainstream tools and strategies are applied in the medical devices sector, which is highly fragmented and contains a high percentage of small companies, and to determine if company size impacts on manufacturing strategy selection.

A questionnaire was developed and disseminated through a number of channels. Responses were received from 38 companies in the UK and Ireland, describing 68 products taken to market in the past five years.

Because of the limited scope of the survey, the findings are indicative rather than conclusive, and interesting trends have emerged. New to the world products were much more likely to exceed company expectations of market success compared to derivative products. It was found that the majority of these innovative products were developed by small companies. Large companies appear to favour minor upgrades over major upgrades even though these prove – on the data presented – to be less successful overall.

These results provide those engaged in this sector with comparative information and some insights for further improvement. The reported trends with respect to company size and product complexity (or degree of novelty) are particularly illuminating. Academically, this sets some expected trends on a firmer footing and unearths one or two unexpected findings.

It is believed that this is the largest survey of determinants of success in UK medical device companies and it provides a comparison with other sectors.

The purpose of this paper is to compare a range of quality and continuous improvement strategies and to investigate whether there is a best choice of strategy for use within the medical devices sector.

A brief literature‐based review of a number of continuous improvement strategies. Comparison of these strategies and a subsequent discussion of the rationale that guides the choice of strategy based on the prevailing conditions. An overview of this process in the context of the medical devices sector is provided.

Quality and continuous improvement strategies can be differentiated in terms of their cultural or process focus. Moreover, the favoured leadership style of an organisation may play a part in determining which strategies are likely to be most appropriate. From the medical device and healthcare product perspective, regulatory and purchasing considerations will have a role in determining the strategy adopted.

For managers seeking to implement a strategy for continuous improvement, a review of organisational leadership styles may help the decision–making process. For the medical devices sector, in particular, the need to align the strategy adopted with regulatory requirements is perhaps self‐evident. However, only by a detailed understanding of the issues involved in continuous improvement, can all of the attendant benefits be gained.

The paper proposes a link between a given organisation's favoured leadership style and the applicability of a particular continuous improvement strategy. The implications for the medical device and healthcare technologies sector are specifically addressed.

Aims to describe a successful use of simulated knowledge worker behaviour used in the developing online procedures and software for arbitration – the E‐Arbitration‐T project

Presents four common factors – deadline, length of task, importance of customer, importance to business – that need to be incorporated within any business process model of knowledge worker behaviour.

A richer model of knowledge worker behaviour is postulated and elements not necessary for the E‐Arbitration‐T model are identified. The knowledge worker's day was defined as being made up of Scheduled, On‐demand and At‐will tasks, only some of which may relate to the business process being modelled. A particular question that must be addressed in this extended model is how to model the choices knowledge workers make between competing at‐will tasks.

The two pieces of work reported here have generated a rich model of knowledge worker behaviour ready for application and refinement in further business process modelling studies.