Kirsikka Grön (2021)
Humanities and Social Sciences Communications, 8, pp. 1-10.
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.