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Data Collection in CGA Evaluation: Analyzing Clinicians’ Practices to Inform Design

Abstract : Comprehensive Geriatric Assessment (CGA) is a multidimensional and multidisciplinary diagnostic instrument that helps provide personalized care to the elderly, by evaluating their state of health. This evaluation is based on extensive data collection about the frail older person’s medical, psychosocial, and functional limitations, in order to develop a coordinated plan to maximize overall health with aging. In the social and economic context of growing ageing populations, medical experts can save time and effort if provided with interactive tools to efficiently assist them in doing CGAs, managing either standardized tests or data collection. Recent research proposes the use of social robots as the central part of these tools. This paper presents the research done to inform the design of such a robot (that is able to interact efficiently with the patient to gather data) and of the clinicians’ application, CGAMed, that allows clinical data management, and discusses the questions raised.
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Conference papers
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https://hal-utt.archives-ouvertes.fr/hal-02896610
Contributor : Jean-Baptiste Vu Van <>
Submitted on : Friday, July 10, 2020 - 4:18:49 PM
Last modification on : Saturday, July 11, 2020 - 3:45:17 AM

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  • HAL Id : hal-02896610, version 1

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Karine Lan Hing Ting, Dimitri Voilmy, Ana Iglesias, Rebeca Marfil. Data Collection in CGA Evaluation: Analyzing Clinicians’ Practices to Inform Design. Workshop Data work in Healthcare 2018, CSCW 2018 - The 21st ACM Conference on Computer-Supported Cooperative Work and Social Computing, New York City's Hudson River, Nov 2018, Jersey City, United States. ⟨hal-02896610⟩

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