Modelling reliability and efficiency of english community pharmacy processes

Naybour, Matthew; Remenyte-Prescott, Rasa; Boyd, Matthew

Abstract

© 2020 IEEE. The research reported in this paper describes a Coloured Petri Net (CPN) method for modelling and analysing reliability and efficiency of the dispensing process in English community pharmacies. The results of CPN simulations are used within an optimisation framework, based on an Ant Colony optimisation (ACO) algorithm, in order to find optimal solutions for a range of process parameters, such as the number of dispensers and pharmacists to employ, prescription checking strategy or staff work pattern. Set-ups are evaluated using a multi-objective utility function with three parameters: the number of prescriptions completed, the number of errors, and the average waiting time. In-field data from 4 English pharmacies are used to control the firing of key transitions of the CPN. The results indicate that if a pharmacy has a large budget the optimal setup is likely to contain many staff, of which a majority will be dispensers. Alternatively, if the budget is small, it is likely the optimal team will be small and contain a majority of pharmacists.

Citation

Naybour, M., Remenyte-Prescott, R., & Boyd, M. (2020). Modelling reliability and efficiency of english community pharmacy processes. https://doi.org/10.1109/RAMS48030.2020.9153661

• Conference Name: 66th Annual Reliability & Maintainability Symposium (RAMS 2020)
• Start Date: Jan 27, 2020
• End Date: Jan 30, 2020
• Acceptance Date: Oct 30, 2019
• Online Publication Date: Jul 31, 2020
• Publication Date: Jan 27, 2020
• Deposit Date: Sep 22, 2020
• Publicly Available Date: Sep 22, 2020
• Publisher: Institute of Electrical and Electronics Engineers
• ISBN: 9781728136899
• DOI: https://doi.org/10.1109/RAMS48030.2020.9153661
• Public URL: https://nottingham-repository.worktribe.com/output/4920247
• Publisher URL: https://ieeexplore.ieee.org/document/9153661
• Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.