Authors: Sadatsafavi M, Bansback N, Zafari Z, Najafzadeh M, Marra C
The Expected Value of Partial Perfect Information (EVPPI) is a theoretically justifiable and informative measure of uncertainty in decision-analytic cost-effectiveness models, but its calculation is computationally intensive as it generally requires two-level Monte Carlo simulation. We introduce an efficient, one-level simulation method for calculation of single-parameter EVPPI. We show that under mild regularity assumptions, the expectation-maximization-expectation sequence in EVPPI calculation can be transformed into an expectation-maximization-maximization sequence. By doing so, calculations can be performed in a single-step expectation using data generated for probabilistic sensitivity analysis (PSA). The new method, though only applicable to single-parameter EVPPI, is fast, accurate, and easy to implement. Further research is needed to evaluate the performance of this method in more complex scenarios and to extend such a concept to similar measures of decision uncertainty.
Status: completed (Link to MEDLINE record)
– The Excel Add-in as a stand-alone file (you will need to bring your PSA data into this file)
– The Excel macro as add-in (to be embedded with your excel file containing PSA results)
Note: The excel add-in comes with an experimental p-value calculation method for each segmentation point. This feature is not part of the manuscript and hence its use is not recommended.
– Code in JAVA (Thanks to David Stefan from UCL)
Keywords: EVPPI, EVPI, Excel