 | Hannah van Kolfschooten Researcher - University of Amsterdam |
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03.04.2024-29.04.2024
EU regulation of Artificial Intelligence in Health: Consequences for Patients' Rights
Expected outcomes
7 published papers + introduction and conclusion for PhD dissertation:
Chapter 1: Introduction
Chapter 2: Paper on The Impact of AI on Trust and Protection of Patients’ Rights
Chapter 3: Paper on Trust, Risk Regulation & Medical Devices Regulation
Chapter 4: Paper on Automated Decision-Making in the GDPR and health
Chapter 5: Paper on the AI Act
Chapter 6: Paper on Case Study on Public Health Surveillance
Chapter 7: Paper on Case Study on Femtech
Chapter 8: Paper on Clinical Decision-Making
Chapter 9: Conclusion
Objectives and Research Questions
It follows that there is a clear need to investigate the impact of these new artificial intelligence-driven technologies on humans and society, particularly in the health sector, and regulate risks of these societal changes. This thesis aims to provide the basis for improving the EU legal and policy framework for algorithmic decision-making in the context of health care and public health in order to strengthen the protection of patients’ rights throughout the EU, while keeping the way open for new AI-driven technologies to improve health care and public health.
This leads to the following main research question: How can EU regulation of algorithmic decision-making in public health and health care be designed in a manner that sufficiently safeguards patients’ rights, specifically the rights to privacy, information and informed consent?
In order to answer this question my PhD-research pursues three main lines of enquiry. The first line is normative:
- How are ‘patients’ rights’ to be understood in the EU context and what normative criteria can be identified to evaluate the level of legal protection of patients in EU Member States?
- How do EU patients’ rights relate to (public, institutional and interpersonal) ‘trust’?
The second line concerns the positive study of the role of the European Union in law and policymaking in the field of algorithmic decision-making in health in light of the normative framework:
- What is the current law and policy on algorithmic decision-making in public health and health care in the EU?
- What are the consequences of the EU’s constitutional limits for law and policymaking in the field of health and algorithmic decision-making?
The third line of enquiry asks what lessons can be drawn from the preceding enquiries for institutional design by taking a legal case study approach:
- How can insights from the preceding inquiries connect to legal practice, both in private, public-private and public settings?
- What do these insights teach about institutional design and the desirability of EU regulation in this field?
Hannah received a LL.M. in Health Law (cum laude, 2018) and a LL.M. in Information Law (cum laude, 2019) from the University of Amsterdam. She also studied at the University of Stellenbosch, South Africa, for a semester. In the 2023 Spring semester, she was a Visiting Researcher in residence at Harvard Law School (Cambridge, Massachusetts) and the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics. Her research stay is funded by Prins Bernhard Cultuurfonds, Dr. Hendrik Muller Fonds, and Stichting Makaria. In the summer of 2023, she was a Visiting Scholar in residence at the University of Verona (Italy).
Next to her research activities, she works as a consultant on medical AI regulation for non-profit organisation Health Action International. She is also the co-chair of the European Commission Thematic Network 2022 on The Impact of Artificial Intelligence on Health Outcomes for Key Populations: Navigating Health Inequalities.
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