Description
Privacy is protected both ethically and legally as a foundation for creating enough trust during clinical encounters for health care decisions to be based on honest discussion and accurate information exchange. Research, public health surveillance, advances in artificial intelligence (e.g., machine learning and predictive algorithms for health care), and the promise of personalized medicine all depend on accurate, complete data. However, health-related data generated and used outside of clinical settings is not protected through privacy regulation. Data aggregators and companies combine data from multiple sources for health and other purposes, while individual behavioral and social practices are being incorporated into medical records. Meanwhile, boundaries and distinctions are breaking down between different categories of protected health data, and between protected data and data collected via commercial apps and services. Privacy of health-related data requires rethinking in this rapidly changing landscape. Panelists will consider challenges in health data privacy, data governance, and privacy policies and practices, including privacy vs the value of data sharing, the adequacy of current legal and regulatory regimes, and how technological developments affect health data privacy.
Learning Objective: To highlight ethical, legal, clinical and practical implications of redefining health data privacy and provide recommendations for improvement.
Authors:
Bonnie Kaplan (Presenter)
Yale University
Elizabeth J. Davidson (Presenter)
University of Hawaii at Manoa
George Demiris (Presenter)
University of Pennsylvania
Richard Schreiber (Presenter)
Geisinger Holy Spirit
Ari Ezra Waldman (Presenter)
New York Law School
Presentation Materials: