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Pervasive Computing Technologies for Healthcare. 15th EAI International Conference, Pervasive Health 2021, Virtual Event, December 6-8, 2021, Proceedings

Research Article

Translating a DC\(^3\)Model into a Conceptual Tool (DCCs Ecosystem): A Case Study with a Design Team

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  • @INPROCEEDINGS{10.1007/978-3-030-99194-4_24,
        author={Tom Ongwere and Erik Stolterman and Patrick C. Shih and Clawson James and Kay Connelly},
        title={Translating a DC\textbackslash(\^{}3\textbackslash)Model into a Conceptual Tool (DCCs Ecosystem): A Case Study with a Design Team},
        proceedings={Pervasive Computing Technologies for Healthcare. 15th EAI International Conference, Pervasive Health 2021, Virtual Event, December 6-8, 2021, Proceedings},
        proceedings_a={PERVASIVEHEALTH},
        year={2022},
        month={3},
        keywords={Discordant chronic comorbidities Designing with experts Design sprints},
        doi={10.1007/978-3-030-99194-4_24}
    }
    
  • Tom Ongwere
    Erik Stolterman
    Patrick C. Shih
    Clawson James
    Kay Connelly
    Year: 2022
    Translating a DC\(^3\)Model into a Conceptual Tool (DCCs Ecosystem): A Case Study with a Design Team
    PERVASIVEHEALTH
    Springer
    DOI: 10.1007/978-3-030-99194-4_24
Tom Ongwere,*, Erik Stolterman, Patrick C. Shih, Clawson James, Kay Connelly
    *Contact email: tongwere1@udayton.edu

    Abstract

    In this paper, we draw inspiration from the Discordant Chronic Comorbidity Care (DC(^3)) model. The model recognizes the complexities of DCCs and incorporates key strategies for assessing and addressing the complexities of DCCs care. We worked with user experience design experts over several design sprints to come up with a conceptual design. It became clear early on that because of the changing DCCs care needs, there is no one-size-fits-all solution for DCCs needs. Thus, the effective care of DCCs requires a holistic approach. The holistic approach involves designers collecting multiple individual tools and mapping those tools to specific needs for DCC care and treatment, which ultimately results in the creation of an ecosystem. We discussed how this ecosystem may be optimized and personalized using machine learning to address individual DCCs needs. Furthermore, putting together these multiple sets of tools could introduce an engineering challenge. We provide strategies and recommendations for future work to address these engineering challenges and how to make a theoretical concept adaptable to technology.

    Keywords
    Discordant chronic comorbidities Designing with experts Design sprints
    Published
    2022-03-23
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-030-99194-4_24
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