Sticking, leaking, flowing: patient perspectives and methods for exploring data uses in the public-private datafied health infrastructure

Abstract As healthcare becomes increasingly datafied, public healthcare systems are becoming more deeply entangled with commercial digital infrastructures. While existing research has examined the political, ethical and infrastructural implications of these developments, less attention has been paid to how patients themselves experience and evaluate health data flows. This article investigates how Danish patients living with chronic illness understand data movement within public-private health infrastructures and explores methodological approaches for eliciting such perspectives. Drawing on five workshops with patients and informed by infrastructural analyses of mobile health apps, we combined written statements, an “attitude compass,” and appscapes (visualisations of app data flows) to facilitate sharing of lived experience, evaluative reasoning and speculation. Analytically, we mobilise the concepts of sticky, leaky and flowing data to characterise patient experiences. Participants frequently described data as “sticky,” becoming stranded across devices, institutions and systems, thereby preventing meaningful circulation to healthcare professionals. Concerns about “leaky” data emerged primarily in relation to speculative reflections on commercial third-party access enabled by digital infrastructures. The findings suggest that contextual legitimacy weighs more heavily than abstract concerns about privacy or public value: When data sharing is perceived as meaningful and potentially life-saving, itis understood as necessary and legitimate.

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Publication Details

Journal
Social Theory & Health
Published
2026-08-21
DOI
https://doi.org/10.1057/s41285-026-00267-8
Primary Topic
COVID-19 Digital Contact Tracing
Type
article
Field-Weighted Citation Impact
0.00

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article

Sticking, leaking, flowing: patient perspectives and methods for exploring data uses in the public-private datafied health infrastructure

Stine Lomborg, Maja Klausen
Social Theory & Health
COVID-19 Digital Contact Tracing
article

Sticking, leaking, flowing: patient perspectives and methods for exploring data uses in the public-private datafied health infrastructure

Stine Lomborg, Maja Klausen
article en

Abstract

Abstract As healthcare becomes increasingly datafied, public healthcare systems are becoming more deeply entangled with commercial digital infrastructures. While existing research has examined the political, ethical and infrastructural implications of these developments, less attention has been paid to how patients themselves experience and evaluate health data flows. This article investigates how Danish patients living with chronic illness understand data movement within public-private health infrastructures and explores methodological approaches for eliciting such perspectives. Drawing on five workshops with patients and informed by infrastructural analyses of mobile health apps, we combined written statements, an “attitude compass,” and appscapes (visualisations of app data flows) to facilitate sharing of lived experience, evaluative reasoning and speculation. Analytically, we mobilise the concepts of sticky, leaky and flowing data to characterise patient experiences. Participants frequently described data as “sticky,” becoming stranded across devices, institutions and systems, thereby preventing meaningful circulation to healthcare professionals. Concerns about “leaky” data emerged primarily in relation to speculative reflections on commercial third-party access enabled by digital infrastructures. The findings suggest that contextual legitimacy weighs more heavily than abstract concerns about privacy or public value: When data sharing is perceived as meaningful and potentially life-saving, itis understood as necessary and legitimate.

Social Theory & HealthVol. 24(1)
University of Copenhagen (DK), University of Southern Denmark (DK)
Syddansk Universitet
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
COVID-19 Digital Contact Tracing
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