Suchergebnisse

"Basierend auf zwei qualitativen Fallstudien von Patientenorganisationen zeigt dieser Artikel auf, wie politisierte und radikale Patientenvertretungen biopolitische Gouvernmentalität, traditionelle Institutionen des Gesundheitswesens als auch deren Macht- und Wissensstrukturen sowie Ausformungen von Subjektivierung durch affirmative biopolitische Strategien infrage stellen. Diese Strategien, so die Autorinnen des Beitrags, bemächtigen die Patientinnen als biologische/r Bürgerinnen aufzutreten, und mittels der Patientenvertretung die vorherrschende Meinung zu Gesundheit und Krankheit durch die Formulierung spezifischer Bürger(rechts)ansprüche neu zu definieren. Dies wiederum erlaubt die Etablierung des/der Patientinnen als aktive Akteurinnen." (Autorenreferat)

Based on a qualitative two-case study of patient-user organizations, this article examines how politicised and radical patient-user organizations can effectively challenge biopolitical governmentality, its medical institutions, as well as its configuration of power/knowledge and forms of subjectivation by using what we consider to be affirmative biopolitical strategies. These strategies, the authors argue, empower the patient as biological citizen because patient-user organizations challenge dominant contemporary views on health and illness by making specific citizenship claims and rearticulate the patient as active agents. Adapted from the source document.

Artificial intelligence (AI) in healthcare promises to make healthcare safer, more accurate, and more cost-effective. Public and private actors have been investing significant amounts of resources into the field. However, to benefit from data-intensive medicine, particularly from AI technologies, one must first and foremost have access to data. It has been previously argued that the conventionally used "consent or anonymize approach" undermines data-intensive medicine, and worse, may ultimately harm patients. Yet, this is still a dominant approach in European countries and framed as an either-or choice. In this paper, we contrast the different data governance approaches in the EU and their advantages and disadvantages in the context of healthcare AI. We detail the ethical trade-offs inherent to data-intensive medicine, particularly the balancing of data privacy and data access, and the subsequent prioritization between AI and other effective health interventions. If countries wish to allocate resources to AI, they also need to make corresponding efforts to improve (secure) data access. We conclude that it is unethical to invest significant amounts of public funds into AI development whilst at the same time limiting data access through strict privacy measures, as this constitutes a waste of public resources. The "AI revolution" in healthcare can only realise its full potential if a fair, inclusive engagement process spells out the values underlying (trans) national data governance policies and their impact on AI development, and priorities are set accordingly.

AbstractBiobanks act as the custodians for the access to and  responsible use of human biological samples and related data that have been generously donated by individuals to serve the public interest and scientific advances in the health research realm. Risk assessment has become a daily practice for biobanks and has been discussed from different perspectives. This paper aims to provide a literature review on risk assessment in order to put together a comprehensive typology of diverse risks biobanks could potentially face. Methodologically set as a typology, the conceptual approach used in this paper is based on the interdisciplinary analysis of scientific literature, the relevant ethical and legal instruments and practices in biobanking to identify how risks are assessed, considered and mitigated. Through an interdisciplinary mapping exercise, we have produced a typology of potential risks in biobanking, taking into consideration the perspectives of different stakeholders, such as institutional actors and publics, including participants and representative organizations. With this approach, we have identified the following risk types: economic, infrastructural, institutional, research community risks and participant's risks. The paper concludes by highlighting the necessity of an adaptive risk governance as an integral part of good governance in biobanking. In this regard, it contributes to sustainability in biobanking by assisting in the design of relevant risk management practices, where they are not already in place or require an update. The typology is intended to be useful from the early stages of establishing such a complex and multileveled biomedical infrastructure as well as to provide a catalogue of risks for improving the risk management practices already in place.

AbstractData practices in biomedical research often rely on standards that build on normative assumptions regarding privacy and involve 'ethics work.' In an increasingly datafied research environment, identifiability gains a new temporal and spatial dimension, especially in regard to genomic data. In this paper, we analyze how genomic identifiability is considered as a specific data issue in a recent controversial case: publication of the genome sequence of the HeLa cell line. Considering developments in the sociotechnological and data environment, such as big data, biomedical, recreational, and research uses of genomics, our analysis highlights what it means to be (re-)identifiable in the postgenomic era. By showing how the risk of genomic identifiability is not a specificity of the HeLa controversy, but rather a systematic data issue, we argue that a new conceptualization is needed. With the notion of post-identifiability as a sociotechnological situation, we show how past assumptions and ideas about future possibilities come together in the case of genomic identifiability. We conclude by discussing how kinship, temporality, and openness are subject to renewed negotiations along with the changing understandings and expectations of identifiability and status of genomic data.

The world is facing an unprecedented public health challenge with the COVID-19 pandemic; this has necessitated numerous efforts being deployed by governments, health agencies and individual institutions – including in the biobanking community – to develop effective tests, toolkits, treatments and vaccines to stem its spread and help fight it. To achieve this goal, the collection, analysis and timely sharing of samples and related data becomes instrumental in collective global research efforts. Aligned to these efforts is the prevalence for automated data processing and digital technologies such as location data and contact tracing applications as part of the toolkits. In this respect, biobanks are important infrastructures for access to these samples and data. Besides availability, quality and technical infrastructures, also ethical, legal and societal issues (ELSI) are particularly crucial in this regard. Public health ethics, personal data protection, ethics of data sharing, protection of consent and vulnerability as well as compliance issues within international data sharing have gained urgency in COVID-19 research. Against this backdrop, BBMRI-ERIC ELSI Services & Research held a webinar that took a closer look at these issues. The webinar took place on April 24th, 2020; the recording is available here. This document not only answers the questions posed during the webinar but ventures into much detail on the topics raised as a result. It also showcases two examples from Germany (presented by Prof. Roland Jahns) and Italy (presented by Prof. Marialuisa Lavitrano), as well as a detailed commentary on contact-tracing-apps from a legal perspective (presented by Gauthier Chassang). The document thus lays the foundation for further discussion on ELSI and COVID-19 in the context of biobanking.