IMI DO->IT have written a rapid review of existing and emerging practices related to informed consent as applied to big data in health care research.
More and more data is being collected by researchers, health care systems and a range of other stakeholders. This data, some of which may be sensitive, offers great opportunities to improve research, health care systems and outcomes, but must be supported by mechanisms that preserve participant data privacy rights.
Due to an evolving data environment – evidenced by changes to data collection, analysis and storage – traditional forms of consent are not always suitable. For example, future use of data and samples might be unknown, and new databases like the Global Rare Disease Patient registry require guidance. As the number of participants and sites involved in research grows, informed consent approaches could better reflect this changing environment.
Approaches to informed consent take a variety of forms including in-person, electronic, written, oral, remote, onsite and combinations of these. Even within the same named models, processes vary and rely on different tools. Approaches also vary in their level of openness of data, as well as the degree of participant control over their data and decisions surrounding their data. Some of the informed consent approaches that were investigated through the rapid review include dynamic consent, retrospective consent and broad consent among many others.