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

doi:10.1145/2493432.2493507

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

Department of Clinical Medicine

74 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. 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.

Original language	English
Title of host publication	Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Publisher	Association for Computing Machinery
Publication date	2013
Pages	133-142
Chapter	10
ISBN (Print)	9781450317702
DOIs	https://doi.org/10.1145/2493432.2493507
Publication status	Published - 2013

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Frost, M., Doryab, A., Faurholt-Jepsen, M., Kessing, L. V., & Bardram, J. (2013). Supporting disease insight through data analysis: refinements of the monarca self-assessment system. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (pp. 133-142). Association for Computing Machinery. https://doi.org/10.1145/2493432.2493507

Supporting disease insight through data analysis: refinements of the monarca self-assessment system. / Frost, Mads; Doryab, Afsaneh; Faurholt-Jepsen, Maria et al.

Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. Association for Computing Machinery, 2013. p. 133-142.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Supporting disease insight through data analysis: refinements of the monarca self-assessment system

Abstract

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