The recent trend toward propertization of health data could pose significant challenges to biomedical research and public health. Property rule systems can result in sizable up-front costs in the acquisition of consent from individual data subjects, as well as the ongoing risk that data subjects will retract consent or object to unanticipated data uses, thus compromising existing data resources and analyses. We argue that property-based approaches to health data should be rejected in favor of liability rule frameworks for the protection of individual privacy interests. We demonstrate that liability rule frameworks for data governance are not only desirable from a theoretical standpoint but have been successfully implemented in the context of two valuable governmental data resources: the Utah Population Database (UPDB) and Statistics Denmark (DST). These case studies suggest that liability models should be considered more broadly for the governance of research using human health data.
Contreras, Jorge L. and Nordfalk, Francisca, "Liability Rules for Health Information" (2018). Utah Law Faculty Scholarship. 129.