OBJECTIVES: To build a flexible and comprehensive long term Type-1 diabetes model incorporating the most up-to-date methodologies (e.g. capturing parameter uncertainty, time profile of patient characteristics and including patient behaviour) to allow a number of cost-effectiveness evaluations. METHODS: An individual patient level discrete event simulation model which includes all the major complications (nephropathy, neuropathy, retinopathy, CVD, PVD, hypoglycaemia, ketoacidosis) and their interactions along with the treatment effects was built based on the developed conceptual model. Patient characteristics (demographics, clinical variables, existing complications and treatment status) are used to estimate the transition probabilities for different events with HbA1c acting as the key variable in the model. Patient behaviour was also incorporated in the cost-effectiveness model by updating HbA1c and other variables in time based on the patient’s behaviour. The model was developed in a flexible manner to allow alternative sets of risk equations to be used and the model is being validated for each set of risk equations. Furthermore, the model is capable of performing probabilistic sensitivity analysis allowing us to capture the effects of parameter uncertainty and report the likelihood that interventions are cost-effective. RESULTS: A number of cost-effective analyses were performed and the trade-offs between costs and QALYs are presented for different treatment/interventions. CONCLUSIONS: The flexible individual patient level discrete event simulation model developed enables cost-effectiveness evaluations of a number of treatments and interventions for Type-1 diabetes. The model allows tracking the history of each of the patients and this enables identification of different sub-groups for targeted interventions. Sensitivity analysis, probabilistic sensitivity analysis and value of information methods will be used to identify the most important parameters in the model.