Applying reliability engineering techniques to the process of community pharmacy dispensing - Naybour, Matthew (2020)
This thesis represents 3 years of research into applying engineering techniques to the community pharmacy dispensing process. The research has been undertaken with the long-term aims of improving the reliability and efficiency of community pharmacy dispensing. A detailed Coloured Petri Net (CPN) model of the dispensing process is con- structed through an iterative process of model design and improvement. The model includes coloured tokens which are used in the CPN to track the dispensing process at a high level of detail. The main novelty of the CPN model developed in this thesis is the ability to model the reliability and efficiency of a healthcare process in a single simulation-based model. Key model outputs related to phar- macy performance include the number of prescriptions dispensed, the number of dispensing errors, and the average waiting time. Results from observations and interviews conducted at 4 UK community pharmacy sites are presented. Quantitative data was collected on the duration of individual stages of the dispensing process, and qualitative interviews about the practice were recorded with practitioners. This data collection represents a novel research contribution, to the field of pharmacy safety and efficiency, since previous work on timing individual stages of the dispensing process has not been carried out before at the same level of detail. The results of a distribution fitting analysis of the data are then used in the CPN model, when simulating a typical UK pharmacy. A modern optimisation framework, Ant Colony Optimisation (ACO), is applied to the CPN model, to ascertain optimal pharmacy set-ups. While using the CPN within the optimisation framework, the CPN model is viewed as a discrete set-up problem, where a number of decision variables are set at discrete values to produce a single pharmacy set-up. Examples of decision variables include the number of dispensers and pharmacists to employ, the checking strategy to use, and the work patten staff should follow. The optimisation problem is to find the best values of these decision variables. The main aspects of novelty in this work are: the use of a three-stage heuristic process, and the combination of CPN and ACO frameworks to tackle a community pharmacy set-up problem. This framework can be used to aid decision makers by providing a Pareto front of non-dominated community pharmacy set-ups to choose from.