eHealth personalization in the next generation RPM systems

Remote patient management (RPM) systems enable (i) monitoring of vital signs of patients at their home, and (ii) providing patients in their homes instructional, educational, or motivational feedback. As such, RPM systems collect a lot of (different types of) data about patients. Although richness of data provides an opportunity for tailoring and personalizing information services, there is a limited understanding of the necessary architecture, methodology, and tailoring criteria to facilitate personalization. In this paper we present (i) a possible next generation RPM system that enables personalization of educational content and its delivery to patients, (ii) introduce a generic methodology for personalization and emphasize the role of knowledge discovery (KDD) and (iii) outline the KDD process with a case study showing an example patient model and adaptation rules.