Simulation models are a valuable tool to model the progression of clinical outcomes for patients over a period of time and are used to estimate lifetime costs and benefits of different interventions. Cohort modelling is a type of simulation model that is used in economic evaluation to represent the experience of a simulated cohort of patients who receive (or do not receive) an intervention. Decision trees and Markov modelling processes are used to estimate the proportion of the cohort who experience health events or health states over time.

Patient level model or micro-simulation is a form of economic modelling where one patient passes through the model at a time. The patient result is stored and the experience of a cohort is obtained by aggregating the individual results. This type of model addresses the memory limitation of Markov models, allowing individual patient histories to be “remembered”, allowing the model to capture diversity in the patient population.

The Health Economics team are currently using simulation modelling to assess health in:

  • Cancer (melanoma)
  • Kidney disease
  • Cardiovascular disease
  • Perinatal care