The topic of Big Data has been explored extensively in various sectors and literature. However, there is still a lack of a framework to guide decision-making that involves ethical issues surrounding the use of big data in health and research.
As part of our new series, #EthicallySpeaking, we’ll share articles on the “Ethics Framework for Big Data in Health and Research” developed under the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative by the NUS Yong Loo Lin School of Medicine’s Centre for Biomedical Ethics.
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Click here for the first article, “Delivering a Practical Framework for Ethical Decision-Making Involving Big Data in Health & Research”, which gives an overview of a body of work relating to the consideration of ethical issues involving big data in health and research.
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Click here for the second article in the series, “An Ethics Framework for Big Data in Health and Research”, which showcases a framework developed by an international working group convened by the SHAPES Initiative.
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The third article in the series, “Openness in Big Data and Data Repositories”, explores the ethical considerations that arise with the sharing of data through online data repositories in health and biomedical research. It also presents a case study for the application of the ethics framework articulated in previous papers. Click here to read more.
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In the fourth installment, we look into the ethical analysis of the use of big data in the field of precision medicine; balancing the benefits of a diverse dataset and the implication of data confidentiality. Click here to read more.
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Real-world data is increasingly important in the clinical research landscape for assessing the safety and effectiveness of health-related interventions. In the fifth installment of the series, we explore the issues related to the quality of data collected and how the ethics framework can be used to manage competing and conflicting interests in the generation of real-world data. Click here to read more.
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With AI set to transform healthcare, the accountability and transparency of decisions made by AI-enabled systems is called into question. The sixth article of the series analyses and applies relevant values identified from the framework to demonstrate how decision-makers can draw on them to develop and implement AI-assisted support systems into healthcare and clinical practice ethically and responsibly. Click here to read more.
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Public-private partnerships could greatly harness and realise the potential of big data in healthcare and research but this could also lead to ethical issues, given the varying – and potentially conflicting – standards, expectations, codes of practice and professional regulations. The seventh article of the series explores how the ethics framework could navigate the conflicts of interests to support the ethical governance of public-private partnerships involving biomedical big data. Click here to read more.
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The collection of biomedical data has been generally assumed to be for the healthcare sector. However, it stands to reason that cross-sectoral sharing of this data could address unmet health and social care needs, improve efficiency of services and reduce costs. If we are to benefit fully from this generated data, it is important to consider which ethical values are at stake and to reflect on ways to resolve emerging ethical issues across ecosystems where values, laws and cultures might be quite distinct. Click here to read the final installment of the series.
