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There is a growing interest in personal health technologies that sample behavioral data from a patient and visualize this data back to the patient for increased health awareness. However, a core challenge for patients is often to understand the connection between specific behaviors and health, i.e. to go beyond health awareness to disease insight. This paper presents MONARCA 2.0, which records subjective and objective data from patients suffering from bipolar disorder, processes this, and informs both the patient and clinicians on the importance of the different data items according to the patient's mood. The goal is to provide patients with a increased insight into the parameters influencing the nature of their disease. The paper describes the user-centered design and the technical implementation of the system, as well as findings from an initial field deployment.