This article is devoted review the process of using new methods of hypertonic disease monitoring. The authors suggest to use patient’s immunological and biochemical homeostasis for predicting and diagnosis this disease. It is proved that these data can be used for monitoring and controlling patients. The correlation between immuno-biochemical parameters and the ecological background patient’s place of residence are set. The problem of the design and construction of specialized complex laboratory control based on client-server architecture is considered. For data analysis supposed to be used statistical and intellectual processing methods. For example, in article describes the basic classification algorithm called “k nearest neighbors”. When the size of “training sample” is sufficient the accuracy in determining the class label reaches 99%. In conclusion emphasizes the importance of developing methods for early diagnosis of cardiovascular disease and using the modern methods for data analysis.