Presentation (CTI)

OBJECTIVES: Discrete event simulation (DES) is a versatile modeling approach used to simulate complex systems where events occur at discrete points in time. In health technology assessment (HTA), they are favored because they can capture time-dependent events, handle individual patient trajectories, and integrate real world data effectively, though its use is often limited by insufficient data for realistic models. While recognized as a valid technique by Canadian Drug Agency (CDA-AMC) guidelines, it is rarely used in HTA. This research examines the CDA AMC database to characterize the frequency, reasons for use, and criticisms of DES models in Canadian HTA.
METHODS: CDA-AMC reimbursement reviews dated 2013 to 2024 were reviewed and included if methods described the use of a discrete-event simulation model structure. Data collected included the decision date, recommendation, treatment, limitations and model style and structure.
RESULTS: Four reviews (covering four unique interventions) for multiple myeloma, chronic heart failure, major depressive disorder, and rheumatoid arthritis were identified. Three received positive recommendations, while one was negative due to concerns about comparative efficacy, high costs, and economic uncertainty. DES was primarily used for its flexibility in modeling treatment sequences, multiple therapy lines, competing risks, heterogeneous populations, and variable event timing based on prior history. Key limitations noted by the committee included a lack of transparency, high model complexity, and concerns about the quality and suitability of data and assumptions.
CONCLUSIONS: The use of DES in Canadian HTA submissions is very rare. However, it is a flexible tool for modeling complex diseases and treatment pathways, as evidenced by positive recommendations in most cases reviewed. Enhancing data quality and improving model transparency could further support the adoption of DES in HTA, enabling more robust evaluations of healthcare interventions.