Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes. With this in mind, the Science and Values Working Group of the COST Action CHIP ME ‘Citizen's Health through (...) public-private Initiatives: Public health, Market and Ethical perspectives’ identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals’ trust in research. We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment. (shrink)

This article explores the evolution of a major longitudinal ‘high risk for schizophrenia’ research programme, started over 50 years ago, which has been largely ignored in recent debates over ‘psychosis risk’ and early intervention. Studying mainly the offspring of individuals with schizophrenia, high-risk investigators aimed to identify a range of precursors of schizophrenia in the hope that the findings would eventually facilitate effective primary prevention. Specifically, the article examines the origins and impact of the pioneering Copenhagen High-Risk Project and thus (...) provides an important contribution to the sparse historical literature on schizophrenia research, including the study of milder conditions and at-risk states in the borderlands of psychosis. (shrink)

The sociological study of knowledge infrastructures and classification has traditionally focused on the politics and practices of classifying things or people. However, actors’ work to escape dominant infrastructures and pre-established classification systems has received little attention. In response to this, this article argues that it is crucial to analyze, not only the practices and politics of classification, but also actors’ work to escape dominant classification systems. The article has two aims: First, to make a theoretical contribution to the study of (...) classification by proposing to pay analytical attention to practices of escaping classification, what the article dubs classification egress. This concept directs our attention not only to the practices and politics of classifying things, but also to how actors work to escape or resist classification systems in practice. Second, the article aims to increase our understanding of the history of quantified and statistical health surveillance. In this, the article investigates how actors in health surveillance assembled a knowledge infrastructure for surveilling, quantifying, and detecting unknown patterns of congenital malformations in the wake of the thalidomide disaster in the early 1960s. The empirical account centers on the actors’ work to detect congenital malformations and escape the dominant nosological classification of diseases, the International Classification of Diseases (ICD), by replacing it with a procedural standard for reporting of symptoms. Thus, the article investigates how actors deal with the tension between the-already-known-and-classified and the unknown-unclassified-phenomenon in health surveillance practice. (shrink)

Many states make use of personal identity numbers to govern people living in their territory and jurisdiction, but only a few rely on an all-purpose PIN used throughout the public and private sectors. This article examines the all-purpose PIN in Finland as a political technology that brings people to the sphere of public welfare services and subjects them to governance by public authorities and expert institutions. Drawing on documentary materials and interviews, it unpacks the history and uses of the PIN (...) as an elementary building block of the Nordic welfare state, and its emerging uses in the post-welfare data economy. The article suggests that, although the PIN is capable of individualizing, identifying, and addressing individuals, its most important and widely embraced feature is the extent to which it enables interoperability among public authorities, private businesses, and their data repositories. Interoperability, together with advances in computing and information technology, has made the PIN a facilitator of public administration, state knowledge production, and everyday life. More recently, in the post-welfare data economy, interoperability has rendered the PIN a national asset in all the Nordic countries, providing a great advantage to biomedical research, innovation business, and healthcare. (shrink)

Throughout the Global North, policymakers invest in large-scale integration of health-data infrastructures to facilitate the reuse of clinical data for administration, research, and innovation. Debates about the ethical implications of data repurposing have focused extensively on issues of patient autonomy and privacy. We suggest that it is time to scrutinize also how the everyday work of healthcare staff is affected by political ambitions of data reuse for an increasing number of purposes, and how different purposes are prioritized. Our analysis builds (...) on ethnographic studies within the Danish healthcare system, which is internationally known for its high degree of digitalization and well-connected data infrastructures. Although data repurposing ought to be relatively seamless in this context, we demonstrate how it involves costs and trade-offs for those who produce and use health data. Even when IT systems and automation strategies are introduced to enhance efficiency and reduce data work, they can end up generating new forms of data work and fragmentation of clinically relevant information. We identify five types of data work related to the production, completion, validation, sorting, and recontextualization of health data. Each of these requires medical expertise and clinical resources. We propose that the implications for these forms of data work should be considered early in the planning stages of initiatives for large-scale data sharing and reuse, such as the European Health Data Space. We believe that political awareness of clinical costs and trade-offs related to such data work can provide better and more informed decisions about data repurposing. (shrink)