Periodic Reporting for period 4 - POLICYAID (Policy, practice and patient experience in the age of intensified data sourcing)
Période du rapport: 2020-12-01 au 2021-11-30
Health services collect, store and use more data than ever before. Healthcare has become data intensive. Clinicians, administrators, politicians, industry and patients have competing ideas about which data to gather, where to send them and how they should be used. This project has explored what is driving this data intensification and mapped the implications for everyday clinical care as well as for the rights and duties of healthcare professionals and patients.
Based on this work, we have described the data politics through which the health services currently take on new responsibilities and tasks and deliver new options for thinking about how to live with data in a productive manner. We have come to describe data as ontologically multiple, meaning that as data are used for every more purposes, they also come to serve as cogs in multiple machines at the same time. Thereby it becomes impossible to identify singular drivers for, or implications of, intensified data sourcing. Rather, we must learn to think with what we call 'data paradoxes': that several ostensibly mutually exclusive stories can be told about data and all be partly true, simply because the same data and databases can be doing very different types of work in different practices, organisational settings, or over time.
Our findings suggest that training in data analysis must now include training in analysing the social dynamics of data reuse, to balance the friction between conflicting uses and to learn to assess the validity of data and how it may change over time. We have developed guidance on the content of such training, we have delivered numerous courses and webinars, and we have shown how these insights will be essential for the long-term sustainability of data-intensive healthcare.
Based on this work, we have described the data politics through which the health services currently take on new responsibilities and tasks and deliver new options for thinking about how to live with data in a productive manner. We have come to describe data as ontologically multiple, meaning that as data are used for every more purposes, they also come to serve as cogs in multiple machines at the same time. Thereby it becomes impossible to identify singular drivers for, or implications of, intensified data sourcing. Rather, we must learn to think with what we call 'data paradoxes': that several ostensibly mutually exclusive stories can be told about data and all be partly true, simply because the same data and databases can be doing very different types of work in different practices, organisational settings, or over time.
Our findings suggest that training in data analysis must now include training in analysing the social dynamics of data reuse, to balance the friction between conflicting uses and to learn to assess the validity of data and how it may change over time. We have developed guidance on the content of such training, we have delivered numerous courses and webinars, and we have shown how these insights will be essential for the long-term sustainability of data-intensive healthcare.
In POLICYAID we employ the term 'intensified data sourcing' to describe contemporary attempts to get more data, of better quality, on more people, while simultaneously making the data available for multiple uses. Data are used for research, for financial remuneration purposes, for quality assurance, for attracting capital and even for police work. POLICYAID investigates how the diverse agendas interact in the making of a new infrastructure for healthcare.
Our aim is to understand the drivers for and implications of intensified data sourcing in the biomedical realm across three levels: policymaking, everyday clinical practices, and citizen experiences of health, illness, rights and duties. To achieve this aim we compare four different forms of intensified data sourcing, and analyse the regulatory frameworks guiding the data procurement and use in Denmark, the EU and beyond.
We fuse anthropological, sociological, legal, and public health scholarship and develop new methodologies for policy analysis by combining document analysis, interviews, participant observation and register-based methodologies. Instead of assuming what data sourcing is about (e.g. surveillance, control or research benefits), we open up the black box of data sourcing by describing how data are selected; financed; what they are used for; how data practices relate to the involved people's hopes and concerns; and who gains which rights to the data. In this way we explore how intensified data sourcing affects clinical routines and patient experience, and understand the preconditions for Big Data research in healthcare.
Our aim is to understand the drivers for and implications of intensified data sourcing in the biomedical realm across three levels: policymaking, everyday clinical practices, and citizen experiences of health, illness, rights and duties. To achieve this aim we compare four different forms of intensified data sourcing, and analyse the regulatory frameworks guiding the data procurement and use in Denmark, the EU and beyond.
We fuse anthropological, sociological, legal, and public health scholarship and develop new methodologies for policy analysis by combining document analysis, interviews, participant observation and register-based methodologies. Instead of assuming what data sourcing is about (e.g. surveillance, control or research benefits), we open up the black box of data sourcing by describing how data are selected; financed; what they are used for; how data practices relate to the involved people's hopes and concerns; and who gains which rights to the data. In this way we explore how intensified data sourcing affects clinical routines and patient experience, and understand the preconditions for Big Data research in healthcare.
The project has shed new light on data intensification processes by way of moving from the high tech research area to the everyday processes of data collection, curation, and analysis, and thereby provided a more realistic basis from which to assess the implications of datafication. Furthermore, the project has identified numerous legal ambiguities and documented an emerging sense of what we call data anxiety among health professionals and researchers. Together the two lines of inquiry will provide the impetus for rethinking regulatory options in the remaining period of the project.