Cancelled: Reflecting Intelligent Transformations in Healthcare: What’s Critical?

Reflecting Intelligent Transformations in  Healthcare: What’s Critical?

Organiser: Kathrin Braun - Research Coordinator for the Center for Interdisciplinary Risk and Innovation Studies (ZIRIUS)

Healthcare, like other critical infrastructures, has become increasingly reliant on and organized through digital technologies, digital data, AI, machine learning, and algorithm-based decision-making. Great hopes and expectations are being associated with the deployment of data and digital arrangements for improved diagnosis and treatment, but also medical research, drug development, public health policy, and healthcare administration.

Whether these hopes materialize and what social challenges and implications these developments involve, however, is currently a matter of contestation. This workshop explores the interrelations between digitalization, datafication, and the reconfiguration of social relationships, practices, and institutional structures in healthcare. We ask: What is critical about the digitalization and datafication of healthcare? What are matters of concern from a social science perspective? We will look at the perspectives and expectations of different stakeholders, the tensions between different purposes of health data collection, the implications of AI and machine learning for medical practice, knowledge production, and the meaning of health and illness, the question of how digitalization and datafication affect the relationships between doctor and patient, treatment and research, healthcare and IT professions, the public and the private sector, and the ethical and governance issues arising in this context.

Program - PDF Workshop Flyer

Abstracts

Klaus Hoeyer (University of Copenhagen)

Data Paradoxes: The Politics of Intensified Data Sourcing in Contemporary Healthcare

In contemporary healthcare, everybody seems to want more data, of higher quality, on more people, and to use this data for a wider range of purposes. In theory, such pervasive data collection should lead to a healthcare system in which data can quickly, efficiently, and unambiguously be interpreted and provide better care for patients, more efficient administration, enhanced options for research, and accelerated economic growth. In practice, however, data are difficult to interpret and the many purposes often undermine one another. Focusing on Denmark, a world leader in healthcare data infrastructures, Klaus Hoeyer shares the perspectives of different stakeholders, from epidemiologists to hospital managers, from patients to physicians, analyzing the social dynamics set in motion by data intensification and calling special attention to that which cannot be easily coded in a database.

Matthias Braun (University of Bonn) 

AI and Health. Ethical and Governance Chances and Challenges 

Different applications of machine learning and deep learning are already changing not only the possibilities of decision-making in the context of disease and health, but are also fundamentally changing our understanding of what we actually mean when we talk about health and disease, but also about justice and solidarity. In the lecture, Matthias Braun will briefly introduce the basic methods of ethical judgment in a first step. In a second step, he will examine examples of the concrete ethical questions that arise in the context of health and illness. Third, he will look at the implications for current regulation and governance in the context of machine learning and deep learning.

Ingrid Schneider (University of Hamburg)

Use of patients’ Treatment Data for Research: Political Challenges and Shifts in Governance

In the course of digitalization in health care, the electronic patient record, the Medical Informatics Initiative, European legal regulations (DGA, EHDS), and data-driven medical research approaches, demands to make patients’ treatment data available for research purposes are rising. In current German and European discussions, we can observe a shift in interpreting the GDPR and medical ethics to legitimize broad use of patients’ data without individual informed consent. This will impact on the doctor-patient relationship, as it requires additional documentation work for doctors in order to collect the data in a structured way. Significant harmonisation and standardization mechanisms will be necessary for interoperability, to allow cross-border use of patient data. Opportunities and risks of these new forms of data governance will be discussed.

Wolfgang Hauser (University of Stuttgart) 

Digitalization in the Health Sector - Results of the TechnikRadar 2022

Digitalization is a driver of change in almost all areas of society, including health. Some associate it with the hope of new therapies thanks to comprehensive access to medical data for research and significantly better health care, while others fear that the growing flood of data will turn them into "transparent patients" once and for all. With whom do citizens want to share which health data? How do doctors assess the impact of digitalization on their work? Answers to such and similar questions can be provided by the TechnikRadar 2022, in the context of which a representative population survey and a survey among doctors on the topic were conducted.

Please contact Mr. Mehdi Mousavian for registration and further information: sayed-mehdi.mousavian@sowi.uni-stuttgart.de