The Ethics of Passive Data and Digital Phenotyping in Neurosurgery

Abstract

Passive data (PD) refers to data generated without any active participation of the subject, such as data from global positioning systems and accelerometers, but also includes metadata on phone call and text activity. As PD can provide unique insight into a patient’s behavior and functioning, it can have numerous applications in neurosurgery, varying from early symptom recognition to postoperative monitoring. The deployment of this technique is, however, associated with substantial ethical challenges. This chapter aims to address these ethical challenges by reviewing the normative ethical literature on this topic. The ethical discussion focusses predominantly on informational privacy, informed consent, and data security; however, significant concerns are also expressed related to regulation of PD products, equity in access, vulnerable patient groups, ownership of the data, and secondary use. The significant degree of consensus in the current ethical literature, the broader empirical evidence supporting the discussed concerns, and the parallels with ethical topics, solutions, and regulations in other medical and nonmedical fields can guide the construction of an ethical framework that ensures a safe and sound implementation of PD in neurosurgery.