Abstract: Many continuous biomedical outcome measures have naturally skewed distributions. Current methodologies for pooling continuous data are limited to methods for combining differences in means or standardised differences in means. These approaches assume normality of the data, and require arithmetic means and standard deviations to be available for each arm of each study. However, skewed outcomes are most appropriately summarised using medians or geometric means. Meta-analyses of skewed outcomes therefore typically necessarily exclude studies which report the most appropriate summary (medians) whilst including studies which use potentially misleading summaries (arithmetic means). It is possible to pool any summary statistic using inverse variance weights if a standard error of the summary statistic is available. Whilst there is no formula for calculating the standard error of a difference in medians estimates of a pseudo standard error may be obtained from measures of uncertainty and statistical significance which may be presented in conjunction with the medians (such as confidence intervals, percentiles and P-values). We will present the results of a simulation study to investigate the statistical properties of a. using arithmetic means for summarising skewed continuous data b. methods of pooling medians using alternative estimates of standard error in relation to the degree of skewness and sample size The alternative methods will be illustrated by application to a real example.