Ethical Considerations When Using a Mobile Eye Tracker in a Patient-Facing Area: Lessons from an Intensive Care Unit Observational Protocol

This article describes the process of designing, approving, and conducting an investigator-initiated protocol to use an eye-tracking device in a health care setting. Participants wore the device, which resembles eyeglasses, in a front-facing manner in an intensive care unit for the study of personnel gaze patterns, producing a visual record of workflow. While the data of interest for our study was not specifically the health information protected by the privacy rule of the Health Insurance Portability and Accountability Act (HIPAA), a wide variety of such data was captured by the eye-tracking device, and the prospective consent of all people who might have been incidentally videotaped was not feasible. The protocol therefore required attention to unique ethical considerations-including consent, privacy and confidentiality, HIPAA compliance, institutional liability, and the use of secondary data. The richness of eye-tracker data suggests various beneficial applications in health care occupational research and quality improvement. Therefore, sharing our study's successful design and execution, including proactive researcher-institutional review board communication, can inform and encourage similarly valuable, ethical, and innovative audiovisual research techniques.

Systematic Redaction for Neuroimage Data

In neuroscience, collaboration and data sharing are undermined by concerns over the management of protected health information (PHI) and personal identifying information (PII) in neuroimage datasets. The HIPAA Privacy Rule mandates measures for the preservation of subject privacy in neuroimaging studies. Unfortunately for the researcher, the management of information privacy is a burdensome task. Wide scale data sharing of neuroimages is challenging for three primary reasons: (i) A dearth of tools to systematically expunge PHI/PII from neuroimage data sets, (ii) a facility for tracking patient identities in redacted datasets has not been produced, and (iii) a sanitization workflow remains conspicuously absent. This article describes the XNAT Redaction Toolkit-an integrated redaction workflow which extends a popular neuroimage data management toolkit to remove PHI/PII from neuroimages. Quickshear defacing is also presented as a complementary technique for deidentifying the image data itself. Together, these tools improve subject privacy through systematic removal of PII/PHI.