  The Expected Value of Sample Information (EVSI) is used to calculate the
economic value of a new research strategy. While this value would be important
to both researchers and funders, there are very few practical applications of
the EVSI. In the main, this is due to computational difficulties associated
with calculating the EVSI in practical health economic models using nested
simulations. We present an approximation method for the EVSI that is based on
estimating the distribution of the posterior mean of the incremental net
benefit across all the possible future samples, known as the distribution of
the preposterior mean. Specifically, we suggest that this distribution is
estimated using moment matching coupled with simulations that are available for
probabilistic sensitivity analysis, which is typically mandatory in health
economic evaluation. We demonstrate that this method is successful using an
example that has previously been applied to other EVSI approximation methods.
We then conclude by discussing how our method fits in with other recent
additions to the literature that detail approximation methods for the EVSI.
