Pfeuffer, Nicolas2022-05-032022-05-032021978-3-88579-713-5https://dl.gi.de/handle/20.500.12116/38622Recently, the management of chronic diseases has advanced to a prime topic for Information Systems (IS) research and practice. With increasing capability of Information Technology, patients are empowered to engage in self-management of chronic diseases connected to promises of health benefits for the individual as well as an unburdening of clinics and economic advantages for health care systems. Nevertheless, patients must be adequately educated about risks, screening and examination options to make patient self-management effective, sustainable and profitable. In this regard, Explainable Artificial Intelligence ((X)AI)-based Patient Education Systems (PES) may be an opportunity to provide patient education in an interactive, intelligible and intelligent manner. By establishing Design Principles (DP) for the engineering of effective (X)AIbased PES, instantiating them in a system prototype and evaluating the DP with the help of general practitioners, this paper contributes to the body of knowledge in designing health IS.enPatient EducationPatient AdherenceExplainable Artificial IntelligenceDesign Science10.18420/wifo2021-121617-5468