Book contents
- AI in eHealth
- Cambridge Bioethics and Law
- AI in eHealth
- Copyright page
- Contents
- Contributors
- Preface
- Acronyms
- 1 Mapping the Digital Healthcare Revolution
- Part I Platforms, Apps and Digital Health
- Part II Trust and Design
- Part III Knowledge, Risk and Control
- Part IV Balancing Regulation, Innovation and Ethics
- 11 Doctors Without Borders? The Law Applicable to Cross-Border eHealth Services and AI-Based Medicine
- 12 Organisational Readiness for the Adoption of Artificial Intelligence in Hospitals
- 13 Regulating the ‘Benefits’ of eHealth
- 14 Data Protection Implications of Forensic Genealogy
- 15 Health Research, eHealth, and Learning Healthcare Systems
- Index
- Cambridge Bioethics and Law
- References
15 - Health Research, eHealth, and Learning Healthcare Systems
Key Approaches, Shortcomings, and Design Issues in Data Governance
from Part IV - Balancing Regulation, Innovation and Ethics
Published online by Cambridge University Press: 08 September 2022
Book contents
- AI in eHealth
- Cambridge Bioethics and Law
- AI in eHealth
- Copyright page
- Contents
- Contributors
- Preface
- Acronyms
- 1 Mapping the Digital Healthcare Revolution
- Part I Platforms, Apps and Digital Health
- Part II Trust and Design
- Part III Knowledge, Risk and Control
- Part IV Balancing Regulation, Innovation and Ethics
- 11 Doctors Without Borders? The Law Applicable to Cross-Border eHealth Services and AI-Based Medicine
- 12 Organisational Readiness for the Adoption of Artificial Intelligence in Hospitals
- 13 Regulating the ‘Benefits’ of eHealth
- 14 Data Protection Implications of Forensic Genealogy
- 15 Health Research, eHealth, and Learning Healthcare Systems
- Index
- Cambridge Bioethics and Law
- References
Summary
The pressure to collect more health data and use that data more effectively is mounting as healthcare systems face greater challenges. However, the risks of increasing health data collection and making our health data work harder are myriad. Given that ‘good outcomes’ in relation to health data usage will be context specific and temporally contingent, the emphasis here is on fit-for-purpose instruments and good practice, acknowledging that health data usage is mediated not only through law, but also through governance structures around data resources themselves. This chapter therefore reviews the Canadian health data ecosystem, examining its federal and provincial legislative elements (with an emphasis on Nova Scotia). It then critiques that ecosystem, bearing in mind the needs of learning healthcare systems. In doing so, it highlights four ecosystem shortcomings, which are grounded in no small part on the perceived competition between private and public interests, and the poor alignment between contemporary data uses and traditional protections associated with autonomy (consent) and privacy (anonymisation). Finally, it offers some key considerations for ecosystem design, addressing specifically social license to operate and the value foundation of both legislation and repository governance instruments.
- Type
- Chapter
- Information
- AI in eHealthHuman Autonomy, Data Governance and Privacy in Healthcare, pp. 423 - 450Publisher: Cambridge University PressPrint publication year: 2022
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