Common good in the era of data-intensive healthcare

Abstract

In recent years, scholars studying data-intensive healthcare have argued that data-driven technologies bind together new actors and goals as part of healthcare. By combining the expectation studies with justification theory, this article adopts a novel theoretical perspective to understand how these actors and goals are enroled in healthcare. Drawing on a case study of Apotti, a Finnish social services and healthcare information system renewal project, the article shows how new emerging health data assemblages stress the aims of producing the common good in public healthcare. The project is studied by analysing interviews of the project’s key actors and various documents produced in the project. The paper shows how, in the collective expectations, the new information system is justified by multiple understandings of the common good, which might be contradictory with each other. Along with the established goals of improving public healthcare operations, the new information system is expected to empower clients and patients, audit and manage personnel, promote national digital social and healthcare service markets, provide better data and tools for research, and promote Finnish research and business in international competition. These expectations are not all based on the settled understanding of the common good of public healthcare as promoting health; the common good is also defined in other terms such as improving research, promoting markets and business, and making Finland famous and a leading country in the digital social services and healthcare field. These goals and expectations are purposely ambiguous to be loose enough to gain attention and maintain it even when the promises are not met. The paper identifies the ambiguity and plurality of the common good as strategies of data-intensive healthcare and raises concerns of how this might shape public healthcare in the future. As the plural understandings of the common good might not support each other, the paper calls for further assessments of how this will affect public healthcare’s core objectives and for seeking solutions that carefully balance the goals of the current and evolving multi-stakeholder environment of data-intensive healthcare.

Emotional labour in the collaborative data practices of repurposing healthcare data and building data technologies

“…The collected empirical material enabled me to situate data practices and data journeys within broader organisational and public–private partnership contexts, which are rarely accessible to the public or the research community. This issue is central due to the increasing importance of public data and new data technologies for managing public organisations and for the delivery of public services (Grön, 2021; Halford et al, 2009; Helén, 2019; Hogle, 2016).…”

“…Via these insights, this study aligns with current scholarship (D’Ignazio and Klein, 2020; Kennedy and Hill, 2018; Pinel et al, 2020; Puig de la Bellacasa, 2011; Taylor, 2020) that has advocated for the recognition of emotions and feelings-based approaches in datafication processes in healthcare for the purpose of challenging rational and neutral perspectives on data practices and data technologies. The recognition of emotions and emotional labour expands the existing scholarship on the tensions and ambiguities inherent in the secondary use of Finnish healthcare data (Aula, 2019; Grön, 2021) and the development of the health data economy (Tupasela et al, 2020). It also facilitates the recognition of the continuous work and meaning making inherent in datafication and shifts attention to its processes rather than its end-products, such as data analytics or data technologies.…”

“…The datafication of healthcare (Hoeyer, 2019; Hogle, 2016; Ruckenstein and Schüll, 2017) has rested upon intensive data work to make healthcare data available for multiple uses and new data technologies (see, e.g. Grön, 2021; Halford et al, 2009). In Finland, like in other Nordic countries, the personal identity number – assigned to all citizens at birth or at immigration – has become a key technology that has enabled data interoperability among public authorities, private businesses and their data repositories (Alastalo and Helén, 2022).…”

“…In doing so, I approached the data practices and building of data technologies as a situated practice (Haraway, 1988) – one that is also collaborative and originates at a particular place and time in discrete social contexts, including in a public–private partnership, one affected by the service economy, and in a Finnish regional healthcare and social service organisation. This situated practice emerges as an interactive process permeated by numerous promises, expectations and goals that might be difficult or impossible to meet (Grön, 2021; Tupasela et al, 2020), therefore evoking emotions.…”

(In)visible everyday work of fostering a data‐driven healthcare and social service organisation

“…The motivation for organisations to become data-driven is rooted in the multifaceted promise of a better future based on the possibilities of data (Hoeyer, 2019) and the collective expectations of technologies (e.g., Grön, 2021). The data-driven delivery of public services and the data-driven management of public organisations is a response to calls for greater efficiency and effectivity in the public sector.…”