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Data Work of Frontline Care Workers: Practices, Problems, and Opportunities in the Context of Data-Driven Long-Term Care

  • Yuling Sun
  • , Xiaojuan Ma
  • , Silvia Lindtner
  • , Liang He*
  • *Corresponding author for this work
  • School of Computer Science and Technology
  • East China Normal University
  • Hong Kong University of Science and Technology
  • University of Michigan, Ann Arbor

Research output: Contribution to journal › Article › peer-review

Abstract

Using data and data technologies to support healthcare has drawn significant attention recently. While CSCW and HCI have largely celebrated the tremendous promise of 'data-driven healthcare' in reforming the healthcare sector, this paper reveals 'labor-driven reality' of this promised data-driven future. Drawing from a qualitative study in a real-world data-driven long-term care (LTC) facility in China, we demonstrate how data-driven technologies work in practice, and especially how frontline workers, as the crux of this data-driven configuration, conduct a tremendous amount of "data work"to make data-drivenness work. This data work, we argue, goes beyond the "clerical work"and functions as a labor of maintenance, articulation, and repair, that both guarantees data technologies' functionalities and acts as an interface between stakeholders. We conclude by discussing the practices, problems and opportunities of this data work in a boarder socio-cultural context.

Original languageEnglish
Article number42
JournalProceedings of the ACM on Human-Computer Interaction
Volume7
Issue number1 CSCW
DOIs
StatePublished - 16 Apr 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • data
  • data work
  • data-driven healthcare
  • data-driven society
  • frontline care worker
  • invisible labor
  • long-term care

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