Big data in health: an ethical framework

The use of Big Data in medical research calls for the widespread collection, dissemination and evaluation of large quantities of personal and confidential information. This entails risks which need to be carefully assessed. To this end, the interdisciplinary team of experts focused on four main areas:

1. Understanding the new types of ethical challenges facing the healthcare industry.
2. Developing guidelines for the ethical evaluation of Big Data projects.
3. Proposing a tool for Research Ethics Committees (RECs) to assess their readiness in Big Data health research.
4. Creating a user-friendly tool for both researchers and ethical oversight mechanisms to ensure responsible Big Data health research and digital health development.

Ever more aspects of human health are being converted into data that can be evaluated both clinically and scientifically. This data can be collected not only by medical specialists but by anyone (with a smartphone, for instance). Current ethical guidelines and policy provisions have fallen behind these rapid developments in the healthcare sector.

This project aimed to develop an ethical framework for Big Data uses in health research. The framework guides the evaluation of ethical questions such as:

• How to ensure responsible Big Data research given the evolving Big Data ecosystem?
• Are the existing ethical standards sufficient to adequately assess Big Data and artificial intelligence (AI) driven projects?
• Are Research Ethics Committees (RECs) effective in fulfilling their role given the emerging challenges in the Big Data context?

This project has a tangible practical impact. The ethics toolkit streamlines ethical assessment. Moreover, the policy recommendations – developed in conjunction with stakeholders and international collaborators – will promote the role of Switzerland as a key player in the global arena of Big Data health research.

Over the past 10 years the research community became increasingly aware of the Big Data and AI-enabled technologies potential in the field of health and medicine. However, the literature reports about technical and methodological challenges, and their ethical implications.

The findings show that privacy is the most debated ethical concern. However, considering data privacy as panacea might translate in overlooking other ethical concerns (e.g., research accountability, fair distribution of benefits, individual autonomy, group-level harm). The fragmented ethical guidance about how to use Big Data and AI-enabled technology increases uncertainty among researchers and developers. This ambiguity is amplified by weak oversight mechanisms, which are challenged by the novelties of Big Data. Indeed, the empirical results collected in the Swiss context expose RECs’ limitations in this field.

The project highlighted gaps in the current regulatory and oversight landscape of Big Data uses for health research and digital health, and it concludes that research oversight mechanisms should be reformed at various levels. The following policy recommendations may help filling existing gaps and streamline the processes that govern ethical data uses:

• Revise and expand the existing ethical standards going beyond data protection and privacy preserving approaches
• Translate scattered and general ethical guidance into actionable practices
• Establish minimum international standards for ethically aligned data uses
• Implement reforms to strengthen the role of the existing oversight mechanisms and improve the review process

As a result of the findings of this project, Swissethics– the umbrella organisation of the Swiss Cantonal Ethics Committees – modified and expanded their templates used by researchers for project submissions.

Finally, we designed an ethics toolkit to help both RECs and researchers reflect on and assess ethical uses of Big Data. For more details about the toolkit, please visit the dedicated website.

• Bioethics

BEHALF - Bigdata-Ethics-HeaLth Framework