通过数据分析支持疾病洞察力:改进monarca自我评估系统

M. Frost, Afsaneh Doryab, M. Faurholt-Jepsen, L. Kessing, J. Bardram
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引用次数: 115

摘要

人们对个人健康技术越来越感兴趣,这种技术可以从患者身上采集行为数据,并将这些数据可视化,以提高患者的健康意识。然而,患者面临的一个核心挑战往往是理解特定行为与健康之间的联系,即超越健康意识到疾病洞察力。本文介绍了MONARCA 2.0,它记录了双相情感障碍患者的主观和客观数据,处理这些数据,并根据患者的情绪告知患者和临床医生不同数据项的重要性。目标是为患者提供对影响其疾病性质的参数的进一步了解。本文描述了以用户为中心的设计和系统的技术实现,以及最初现场部署的结果。
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Supporting disease insight through data analysis: refinements of the monarca self-assessment system
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.
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