The history of knowledge based systems in medicine has been that they are generally very localised, serving a special need in a single setting. Very few have proven to be capable of transfer to a distant environment. With the advent of tele-medical services and the associated transfer of data and knowledge in such services, the ability of medical KBS to transfer will be crucial to the success of tele-medical services. Differences in knowledge acquisition methods, knowledge representation techniques and in the epidemiological composition of training databases may influence viable transfer of knowledge based systems. Through experiments we demonstrate how rule-based systems may impose inflexible demands on data, how different knowledge acquisition techniques acquire different aspects of knowledge, though trained on a common training database, and how different knowledge acquisition techniques show varying degrees of robustness to slight changes in training databases.