In this paper, we propose a tree-based method for multivariate outcomes consisting in a mixture of categorical and continuous responses. The split function for tree-growing is derived from a likelihood based approach for a general location model (GLOM). One situation where the new approach should be appealing is when mixed types multiple outcomes are used as surrogates for an unobserved latent outcome. An illustration of the application of the new method is given with health care data extracted from an administrative database.