INDIVIDUAL-LEVEL STATE-TRANSITION MODELING USING EXCEL AND VBA

Format Requirements: The course will include a combination of didactic lectures and hands-on exercises. This course is designed for those with basic understanding of decision analytic modeling (e.g. comfortable with introductory modeling courses offered at SMDM meetings) and interested in building relatively complex models. It is recommended that participants bring a computer with Microsoft Excel installed. Familiarity with VBA macros is highly recommended but not necessary.

• Understand the differences between cohort versus individual-level state-transition models.
• Understand biases with cohort-based models because of non-linear relationship between the model inputs and outcomes, and how individual-level STMs can incorporate heterogeneity in data.
• Learn the concepts of Monte Carlo simulation and its implementation in Excel to solve STMs.
• Learn the advantages of using variance reduction techniques such as common random numbers to reduce first-order uncertainty, and construction of common random numbers using VBA macros.
• Learn methods to reduce the computational burden of conducting probabilistic sensitivity analysis using stratified sampling methods.
• Learn challenges of conducting probabilistic sensitivity analysis (PSA) in individual-level STMs because of two levels of uncertainty—the natural variability of individual outcomes in patients (first-order or stochastic uncertainty) and uncertainty in the probabilities that estimate those outcomes (termed second-order, or parameter uncertainty).
• Learn plotting methods to present sensitivity analysis results in Excel.

Hands-on exercise: The course participants will get an opportunity to implement the above methods in Excel. The hands-on-exercises will allow participants to build a simple individual-level STM in Excel, implement the use of common random numbers using VBA macros, plot tornado diagrams in Excel, generate inputs for PSA, and plot cost-effectiveness acceptability curves.