Addressing Privacy and Ethics requirements in connected healthcare and IoT systems design and development is vital to develop trust in using IoT based systems in the healthcare domain. IoT based connected healthcare systems require an appreciation of both the ethico-legal milieu and the sociopolitical landscape.
This workshop will convene stakeholders from healthcare providers, medical device manufacturers, research, patient advocates, regulators and payors involved in the design and development of connected health systems. Workshop participants will explore the latest technologies, challenges, and regulations regarding privacy, ethics and trust for connected health IoT systems, and make recommendations for the future. The learning outcomes and topics for discussion will include but are not limited to:
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Identifying data protection and privacy consideration when designing and developing new devices and connections to legacy systems and devices, to improve trust among people using IoT devices and systems, and trust in device to device connections.
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Identification of the ethical issues that need to be addressed with connected health IoT. E.g Individual rights; autonomy, privacy and confidentiality; ownership of the data; necessity and proportionality; beneficence and nonmaleficence. How do we satisfy these ethical requirements in designing and developing connected health IoT solutions?
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Identification of frameworks, standards and legal regulations related to privacy in connected health IoT based system.
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Examples of good practices, lessons learned, successful products, projects, services, and pertinent stories related to connected healthcare privacy, ethics and trust.
Preparatory pre-reads: Data Responsibly Comics (Web)
Keynote Panelists:
- Dr. Julia Stoyanovich, Assistant Professor in the Department of Computer Science and Engineering at the Tandon School of Engineering and the Center for Data Science, New York University
- Shaneel Pathak, CEO and cofounder of Zoe Insights
- Dr. Jeannette Wing, Avanessians Director of the Data Science Institute and Professor of Computer Science at Columbia University