Digital phenotyping and sensitive health data: Implications for data governance

Mobile and wearable devices, such as smartwatches and fitness trackers, increasingly enable the continuous collection of physiological and behavioral data that permit inferences about users ’ physical and mental health. Growing consumer adoption of these technologies has reduced the cost of generating clinically meaningful data. This can help reduce medical research costs and aid large-scale studies. However, the collection, processing, and storage of data comes with significant ethi cal, security, and data governance considerations. A complex ecosystem is developing, with the need for collaboration among researchers, healthcare providers, and a broad range of entities across public and private sectors, some of which are not traditionally associated with health care. This has ra ised important questions in the literature regarding the role of the individual as a patient, customer, research participant, researcher, and user when consenting to data processing in this ecosystem.1 Here, we use the emerging concept of “digital phenotyping”2 to highlight key lessons for data governance that draw on parallels with the history of genomics research, while highlighting areas in which digital phenotyping will require novel governance frameworks.

Source: Journal of the American Medical Informatics Association - February 27, 2021 Category: Information Technology Source Type: research