Towards Ethical Data Sharing Solutions for Resilient Healthcare Systems

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Lem Ngongalah | Research Analyst
Amelia Williams | Research Communications Officer

Date: 15 February 2024

Many people familiar with the world of tech have heard the phrase “data is the new oil.” It’s easy to dismiss the saying as a celebration of techno-capitalism’s most promising (and least ethical) revenue stream, but the analogy extends beyond profit. Both have the potential to power society. Data is often locked away—in organisational siloes, incompatible formats, filing cabinets—the same way oil was hidden for eons within the Earth’s crust. But unlike oil, we don’t want the pioneers of data extraction to be unregulated industrialists. At Trilateral’s Health cluster, the question of ethical data sharing, use, and management is a core component across all of our work.

Why grapple with the data issue? For decades, individual organisations, be they hospitals, regional authorities, or social services, have collected data about the patients and populations under their purview. If analysed together, these datasets could give researchers a bird’s-eye-view of trends, threats, and shifts in public health. But for a long time, these data were too large for researchers to analyse, minimising their impact on public health decision-making. Today, many of the most promising healthcare innovations employ AI models capable of analysing these massive datasets, producing insights which could transform societal responses to pandemics, natural disasters, and chronic diseases. Despite this promise, best practices for healthcare data sharing remain vague and unclear, slowing the deployment of new technologies and leaving a legal grey area in which unethical practices could flourish.

The challenge

The development of data-driven healthcare tools faces significant hurdles, chief among them being data siloes and data sharing. Some of the main challenges associated with data sharing in the health domain include:

  • Data siloes. Often, valuable data is confined in isolated siloes; for example, individual hospitals or local health authorities store datasets containing valuable insights that could enable researchers to develop a comprehensive view of public health. However, due to the lack of established data sharing frameworks, this data often sits unused.
  • Lack of interoperability. Different countries and organisations store data using varied systems, platforms, and formats, requiring manual conversion into a compatible format for analysis, which is laborious and time-consuming. This slows the identification of trends and critical insights necessary to support effective decision-making.
  • Ethical and legal uncertainty. The GDPR defines data rights and obligates data controllers and processors to handle sensitive data, such as health information, securely and transparently. However, safe routes to data sharing are less clear, leaving organisations uncertain about how they can safely transfer data without violating data laws, privacy rights, and other legal and ethical considerations.
  • Scepticism about data sharing. Varying attitudes toward data privacy, transparency, and trust impact willingness to share data. For example, hospitals may be reluctant to share detailed information on deaths, fearing that data or the results of audits could be misinterpreted by the public and attract unwarranted scrutiny, or raise ethical or legal concerns.

Overcoming these hurdles requires researchers to strike a delicate balance between the need to safeguard privacy and the necessity to facilitate data sharing to enable collaboration, innovation, and cooperation between authorities.

Lessons from PANDEM-2: Recommendations for better data sharing practices

Trilateral participated in the EU-funded PANDEM-2 project, which developed a prototype pandemic preparedness training system for EU member states. The project encountered difficulties in data availability, particularly in epidemiological data, due to variations in data sharing policies and protocols. In an effort to contribute to the ongoing discourse on data sharing for effective pandemic preparedness in the EU, Trilateral led the development of a series of recommendations to facilitate data sharing and enhance cross-border collaboration, drawing on lessons learnt from the project.

  • Establishment of standardised data collection methods. Collaborative efforts are crucial to establish common data standards which can facilitate data sharing by ensuring consistency, compatibility, and ease of integration.
  • Development of a common legal framework. This framework should emphasise lawful data sharing, with comprehensive guidelines on data ownership, privacy, and security, and reinforce GDPR provisions allowing for lawful data sharing, highlighting data encryption, anonymisation, transparency, and accountability.
  • Implement secure and privacy-preserving unique patient identifiers within national health systems. This would standardise patient data and enhance data sharing and analysis in future public health crises by enabling more accurate tracking of health outcomes, risk factors, and the development of targeted interventions.
  • Implement privacy-protecting tools. These tools, such as federated learning, a decentralised approach which does not require data to be compiled and stored centrally, enable secure access to health data without compromising privacy, facilitating collaborative research and more effective decision-making.
  • Governance. Governance to facilitate efficient data sharing would improve the delivery of public health services. The creation of a central governing entity within the EU Health Union framework to 1) manage data sharing between member states, 2) harmonise data sharing practices, 3) monitor GDPR compliance, and 4) implement data protection measures would enhance the EU’s capacity to respond to health crises.

These insights align with the EU’s efforts in promoting data sharing in the EU, and offer potential lessons for the European Health Data Space, highlighting the need for collaborative solutions to enhance preparedness in public health initiatives.

Today, the world faces myriad public health threats, driven by climate change, globalisation, and conflict. Rapidly developing technology offers solutions—or at least more effective approaches—to these crises. However, the deployment of these potentially transformative tools is often hindered by poor data sharing practices; organisational, regulatory, and administrative inefficiencies that hamper innovation and prevent the uptake of emerging technologies with life-saving capabilities. Trilateral’s Health cluster is focused on the development of robust solutions which incorporate the principles of ethics- and privacy-by-design to facilitate the development of responsible, trustworthy, and ethical AI solutions which meet the practical needs of the real world without compromising on social and legal values. To learn more about our work, visit

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