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Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent

Author

Listed:
  • Jeremy D. Goldhaber-Fiebert

    (Department of Health Policy, Stanford School of Medicine, Stanford, CA, USA
    Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA)

  • Hawre Jalal

    (School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada)

  • Fernando Alarid-Escudero

    (Department of Health Policy, Stanford School of Medicine, Stanford, CA, USA
    Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA)

Abstract

Purpose Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized. Methods We compare iSTM-produced estimates of decision uncertainty and VOI to corresponding cSTMs. For a 2-alternative decision and normally distributed incremental costs and benefits, we derive analytical expressions for the probability of being cost-effective and the expected value of perfect information (EVPI) for cSTMs and iSTMs, accounting for correlations in incremental outcomes at the population and individual levels. We use numerical simulations to illustrate our findings and explore the impact of relaxing normality assumptions or having >2 decision alternatives. Results iSTM estimates of decision uncertainty and VOI are biased but asymptotically consistent (i.e., bias approaches 0 as number of microsimulated individuals approaches infinity). Decision uncertainty depends on 1 tail of the INMB distribution (e.g., P[INMB

Suggested Citation

  • Jeremy D. Goldhaber-Fiebert & Hawre Jalal & Fernando Alarid-Escudero, 2025. "Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent," Medical Decision Making, , vol. 45(2), pages 127-142, February.
  • Handle: RePEc:sae:medema:v:45:y:2025:i:2:p:127-142
    DOI: 10.1177/0272989X241305414
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    References listed on IDEAS

    as
    1. Anthony O'Hagan & Matt Stevenson & Jason Madan, 2007. "Monte Carlo probabilistic sensitivity analysis for patient level simulation models: efficient estimation of mean and variance using ANOVA," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1009-1023, October.
    2. Anirban Basu & David Meltzer, 2007. "Value of Information on Preference Heterogeneity and Individualized Care," Medical Decision Making, , vol. 27(2), pages 112-127, March.
    3. Anthony O'Hagan & Matt Stevenson & Jason Madan, 2007. "Monte Carlo probabilistic sensitivity analysis for patient level simulation models: efficient estimation of mean and variance using ANOVA," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1009-1023.
    4. Hawre Jalal & Jeremy D. Goldhaber-Fiebert & Karen M. Kuntz, 2015. "Computing Expected Value of Partial Sample Information from Probabilistic Sensitivity Analysis Using Linear Regression Metamodeling," Medical Decision Making, , vol. 35(5), pages 584-595, July.
    5. Stefano Conti & Karl Claxton, 2009. "Dimensions of Design Space: A Decision-Theoretic Approach to Optimal Research Design," Medical Decision Making, , vol. 29(6), pages 643-660, November.
    6. Tae Yoon Lee & Paul Gustafson & Mohsen Sadatsafavi, 2023. "Closed-Form Solution of the Unit Normal Loss Integral in 2 Dimensions, with Application in Value-of-Information Analysis," Medical Decision Making, , vol. 43(5), pages 621-626, July.
    7. Stavroula A. Chrysanthopoulou & Carolyn M. Rutter & Constantine A. Gatsonis, 2021. "Bayesian versus Empirical Calibration of Microsimulation Models: A Comparative Analysis," Medical Decision Making, , vol. 41(6), pages 714-726, August.
    8. Fernando Alarid-Escudero & Richard F. MacLehose & Yadira Peralta & Karen M. Kuntz & Eva A. Enns, 2018. "Nonidentifiability in Model Calibration and Implications for Medical Decision Making," Medical Decision Making, , vol. 38(7), pages 810-821, October.
    9. Eline M. Krijkamp & Fernando Alarid-Escudero & Eva A. Enns & Hawre J. Jalal & M. G. Myriam Hunink & Petros Pechlivanoglou, 2018. "Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial," Medical Decision Making, , vol. 38(3), pages 400-422, April.
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