In psychiatry, the assessment of outcome, to be relevant for clinical practice, should be multidimensional. This demands suitable statistical tools both to represent and to analyse the complex relationships between variables. This paper aims to provide guidelines for selecting graphical displays of multidimensional data that enable better capturing of the relationships between variables and summarize information available for individual cases as well as for groups of patients. Multivariate graphical techniques such as Chernoff faces, stars, parallel co-ordinates and Andrews plots are applied to a set of data drawn from the South Verona Outcome Project, a naturalistic study based on a multidimensional model for the assessment of outcomes, routinely conducted at the Institute of Psychiatry of the University of Verona, Italy. The assessment includes global functioning, psychopathology, social disability, subjective quality of life, and satisfaction with services, number of service contacts and days of hospitalization.The selected sequence of graphical displays allows a quick understanding of the multivariate data set not otherwise obtainable with numerical indexes and specifically enabled us to: (a) picture the characteristics of the data set on each single variable; (b) identify relationships between two or more variables; (c) identify peculiarities of individual patients and of group of patients. In psychiatry and in other areas of medicine a graphical approach to multidimensional data is a useful analytical tool for increasing the impact of outcome studies, in everyday clinical practice and in monitoring and evaluating of services.