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Economic Evaluation Results Are Substantially Affected by Parameter Input Correlation.

Erin Barker1, Harriet Fewster1, Karina Watts1

  • 1York Health Economics Consortium, University of York, York, North Yorkshire, UK.

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
|May 2, 2025
PubMed
Summary
This summary is machine-generated.

Probabilistic sensitivity analysis (PSA) requires careful consideration of parameter correlation. Ignoring correlations can lead to inaccurate estimates of cost-effectiveness certainty, impacting decision-making.

Keywords:
Markov modelcost-effectiveness analysisparameter correlationprobabilistic sensitivity analysis

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Area of Science:

  • Health Economics
  • Decision Science
  • Statistical Modeling

Background:

  • Probabilistic sensitivity analysis (PSA) is crucial for quantifying uncertainty in cost-effectiveness analysis (CEA).
  • The impact of input parameter correlation on PSA outcomes is often underestimated or omitted.
  • This oversight can lead to misestimation of uncertainty and flawed conclusions in CEA.

Purpose of the Study:

  • To develop a simplified model for assessing the influence of input parameter correlation on the incremental cost-effectiveness ratio (ICER).
  • To evaluate the effect of correlation on the probability of an intervention being cost-effective.
  • To highlight the importance of accounting for inter-parameter correlations in PSA.

Main Methods:

  • Development of a Markov model incorporating three correlation scenarios: none, partial, and perfect.
  • Utilization of a hypothetical case study to demonstrate the impact of each correlation approach.
  • Application of scenario analyses to ensure the robustness of findings across different conditions.

Main Results:

  • The incremental cost-effectiveness ratio (ICER) remained relatively consistent across different correlation assumptions.
  • The degree of certainty in decision outcomes varied significantly, with no correlation yielding the most certain results and perfect correlation the least.
  • The proximity of the ICER to the willingness-to-pay threshold modulated the influence of correlation on PSA outcomes.

Conclusions:

  • The method used to model parameter correlation in PSA significantly affects the certainty of model outputs.
  • Failure to account for inter-parameter correlation can result in over- or underestimation of cost-effectiveness certainty.
  • Researchers and decision-makers must carefully consider the implications of parameter correlation in PSA for reliable economic evaluations.