<p>Discrete event simulation (DES) provides enhanced flexibility over modelling techniques that have been traditionally used for assessing health-economic outcomes, making it a particularly interesting technique for modelling complex clinical pathways. Discrete event simulation also facilitates consideration of resources and capacity constraints, making it suitable for addressing a wide range of research questions in health care and beyond. However, those unfamiliar with DES often perceive it to be more complex compared to traditional health-economic modelling techniques, such as state-transition modelling. To address this perceived complexity, this tutorial provides a detailed illustration of implementing DES in the open-source R software using the simmer package, through a case study in colon cancer. The tutorial is aimed at those who have a conceptual model that they want to implement as a DES in R, and are looking for practical guidance. It discusses methodological aspects related to DES and individual-level modelling in general that have not been extensively covered in literature, the conceptual model structure and corresponding pseudocode, data analysis, model implementation, and the deterministic and probabilistic analysis of the model. The documented code provides all building blocks required to develop a wide range of DES models in R using the simmer package.</p>