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Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note.

Benjamin P Geisler1, Uwe Siebert, G Scott Gazelle

  • 1Institute for Technology Assessment, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA. ben@mgh-ita.org

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
|July 24, 2008
PubMed
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This study introduces a method to automate one-way deterministic sensitivity analyses for Monte Carlo microsimulation models. This facilitates easier interpretation of complex decision-analytic models, enhancing the use of TreeAge Markov models.

Area of Science:

  • Decision-analytic modeling
  • Computational statistics
  • Health economics modeling

Background:

  • Monte Carlo microsimulations are increasingly used in decision-analytic modeling due to their ability to handle discrete events.
  • Deterministic sensitivity analyses are crucial for interpreting simulation results but are challenging to integrate with Monte Carlo methods in standard software.
  • Existing methods require significant time investment for combining these analyses.

Purpose of the Study:

  • To develop a method for facilitating one-way deterministic sensitivity analysis in TreeAge Markov state-transition models that utilize first-order Monte Carlo simulations.
  • To streamline the process of sensitivity analysis for complex simulation models.

Main Methods:

  • Developed a generic script using Microsoft Visual Basic for Applications (VBA) integrated with EXCEL.

Related Experiment Videos

  • Utilized TreeAge Pro Suite 2007 for constructing the Markov state-transition models.
  • Created a user-friendly EXCEL worksheet to accompany the script, minimizing the need for programming expertise.

    • Main Results:

    • Successfully created an automated system for performing one-way deterministic sensitivity analyses within EXCEL for microsimulation models.
    • The developed script and worksheet enable users with limited programming knowledge to conduct these analyses efficiently.
    • Demonstrated the feasibility of linking TreeAge Pro Suite 2007 with Visual Basic for automated analysis.

    Conclusions:

    • Linking TreeAge Pro Suite 2007 and Visual Basic effectively enables deterministic sensitivity analyses for first-order Monte Carlo simulations.
    • The developed approach simplifies a complex analytical process, potentially saving considerable time and resources.
    • The methodology holds potential for broader applications in automated analysis of simulation models.