A systematic review of simulation models in medicine supply chain management : current state and emerging trends

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Nabayiga, Hellen and van der Meer, Robert and Ali Agha, Mouhamad Shaker (2025) A systematic review of simulation models in medicine supply chain management : current state and emerging trends. Decision Analytics Journal, 14 (2025). pp. 1-12. 100555. ISSN 2772-6622 (https://doi.org/10.1016/j.dajour.2025.100555)

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Abstract

Simulation modelling has widely been applied in healthcare supply chain management, focusing on blood and vaccine supply chains with less attention on the medicine supply chains. This study presents a systematic review of studies applying simulation methods, namely agent-based modelling, discrete event simulation, and system dynamics, to address problems in the medicine supply chain. We adopt the Search, Appraisal, Synthesis, and Analysis (SALSA) approach to collect data from three databases (Scopus, Web of Science, and PubMed) from 2000 to 2023. 320 journal publications qualified for the initial screening and filtration and were extracted for further analysis. Only 31 studies met the inclusion criteria, with the first publication identified in 2010 and the last in 2023. The paper shows the usefulness of applying simulation in identifying medicine supply chain bottlenecks pertaining to stockouts (19%, n = 6), and falsified or counterfeit (16%, n = 5). System dynamics was the most applied approach with 42% (n = 13) and 6% (n = 2) employing a hybrid simulation approach. 32% (n = 10) of the studies reported verification and validation at either a conceptual or operational level with insufficient data from the real-world system reported as a challenge. The study suggests a gradually increasing interest in simulation applications in medicine supply chains informing decision-making. Combining multiple simulation approaches is recommended to address complex medicine supply chain issues, such as availability. In order to understand the usefulness of the model in decision-making, more effort is needed to validate developed models.

ORCID iDs

Nabayiga, Hellen, van der Meer, Robert ORCID logoORCID: https://orcid.org/0000-0002-9442-1628 and Ali Agha, Mouhamad Shaker ORCID logoORCID: https://orcid.org/0000-0002-9143-7990;
CORE (COnnecting REpositories)