An Ethics Framework for Big Data in Health and Research

Area of Science:

• Bioethics
• Health Informatics
• Data Science

Background:

• Ethical decision-making frameworks are crucial for navigating complex issues in big data.
• Big data in health and research presents unique ethical challenges regarding use, sharing, and reuse.
• Existing frameworks may not adequately address the specific values and concerns inherent in health-related big data.

Purpose of the Study:

• To present a novel Ethics Framework for Big Data in Health and Research.
• To outline the rationale and ethical concerns underpinning the framework.
• To provide a structured approach for addressing ethical issues in big data applications.

Main Methods:

• Development of a framework by a working group from the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative.
• Identification of substantive and procedural values for ethical consideration.
• Description of a step-by-step process for ethical issue resolution in big data.

Main Results:

• The paper details an Ethics Framework for Big Data in Health and Research.
• It outlines key ethical concerns and proposes a set of values for consideration.
• A systematic process for ethical decision-making in big data contexts is presented.

Conclusions:

• The developed framework provides a methodical approach to ethical decision-making for big data in health and research.
• It supports the responsible use, sharing, and reuse of health data.
• The framework serves as a foundation for addressing ethical challenges across various big data domains.