Ant colony optimisation of a community pharmacy dispensing process using Coloured Petri-Net simulation and UK pharmacy in-field data

Abstract

There are 11,619 community pharmacies in England which dispense over 1 billion prescriptions each year, providing essential primary care to NHS (National Health Service) patients. These pharmacies are facing pressure from a number of sources including funding cuts and high demands on services, while trying to deliver the highest standards of care. This paper presents an optimisation of a Coloured Petri Net (CPN) community pharmacy simulation model using an Ant Colony Optimisation (ACO) method. The CPN method was proposed by Naybour et al . Quantitative data from UK community pharmacies was collected by the authors and incorporated into the CPN simulation model. The optimisation is made up of a choice of how many staff to employ, which prescription checking strategy to use, and which staff work pattern to implement. This method aims to provide decision makers with a set of optimal pharmacy configurations at different cost levels. This can help to support pharmacy safety, efficiency, and improve decision making processes. It has been demonstrated how reliability modelling techniques traditionally used in safety-critical industries, can be used to carry out safety and efficiency analyses of healthcare systems, such as dispensing processes in community pharmacies, illustrated in this contribution.