Facing the increasing demands and challenges in the area of chronic disease care, various studies on the healthcare system which can, whenever and wherever, extract and process patient data have been conducted. Chronic diseases are the long-term diseases and require the processes of the real-time monitoring, multidimensional quantitative analysis, and the classification of patients' diagnostic information. A healthcare system for chronic diseases is characterized as an at-hospital and at-home service according to a targeted environment. Both services basically aim to provide patients with accurate diagnoses of disease by monitoring a variety of physical states with a number of monitoring methods, but there are differences between home and hospital environments, and the different characteristics should be considered in order to provide more accurate diagnoses for patients, especially, patients having chronic diseases. In this paper, we propose a patient status classification method for effectively identifying and classifying chronic diseases and show the validity of the proposed method. Furthermore, we present a new healthcare system architecture that integrates the at-home and at-hospital environment and discuss the applicability of the architecture using practical target services.