Models and Tools
Scan selected model-based analyses. Explore modeling methods and tools.
Cardiovascular Disease Model
The Cardiovascular Disease (CVD) Prevention Model is used to compare the health and economic consequences of alternative screening, prevention, and treatment strategies in the United States. The model captures lifestyle and environmental risk factors that influence CVD outcomes. More on the CVD model.
Modeling Maternal Mortality
The maternal mortality policy model is empirically calibrated to country-specific data and is used to compare the health benefits and economic consequences of different strategies to prevent maternal mortality. Analyses are intended to provide actionable information to decision makers. More on the maternal model.
Featured: Models and Guidelines
Featured: Bayesian Calibration
FREQUENTLY ASKED QUESTIONS
Why are models used in decision analysis?
Models are used to understand an underlying process that may be unobserved, or to extrapolate current evidence over a longer time frame. Decisions may affect people for years to come whereas most clinical trials only run for a couple of years–modeling allows current evidence to be projected into the future.
What is a markov model?
Used in many disciplines, markov models describe a process where the probability of moving from one state of being to another only depends on your current state–in other words, history doesn’t matter. In health, markov models are typically used to understand disease progression over time.
What is model calibration?
Model calibration is a process in which we refine model parameters (i.e., inputs) so that our model output matches up with other data – so it gives us output that we expect to see. In calibration we force our model to align with empiric data describing the underlying process to make it more accurate.