Decision support systems that help physicians are becoming very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate, reliable and quick response. One of the most viable among models are decision trees, already successfully used for many medical decision making purpose. Although effective and reliable, the traditional decision tree construction approach still contains several deficiencies. The real-world problem that was a background of our research, has a special structure. According to the same attributes we have to determine five different decisions. We decided for two different approaches: the traditional decision trees and a completely new approach of multiple-outcome decision making where we get a decision vector as a result of the decision tree. For constructing such decision trees we used evolutionary programming and we have developed a SW tool named DecRain. A comparison between developed models and obtained results has shown that our approach can be considered as a good choice for different kinds of real-world medical decision making.