Supporting Disease Insight through Data Analysis: Refinements of the MONARCA Self-Assessment System

Mads Frost, Afsaneh Doryab, Maria Faurholt-Jepsen, Lars Vedel Kessing, Jakob Bardram

87 Citations (Scopus)

Abstract

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. How- ever, 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 ob- jective data from patients suffering from bipolar disorder, pro- cesses this, and informs both the patient and clinicians on the importance of the different data items according to the pa- tient’s mood. The goal is to provide patients with a increased insight into the parameters influencing the nature of their dis- ease. The paper describes the user-centered design and the technical implementation of the system, as well as findings from an initial field deployment.
Original languageEnglish
Title of host publicationSupporting Disease Insight through Data Analysis: Refinements of the MONARCA Self-Assessment System
PublisherAssociation for Computing Machinery
Publication date2013
ISBN (Print)9781450317702
DOIs
Publication statusPublished - 2013

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