Identifying opportunities and threats to the right to health in a new data-driven economy.
The application of Big Data, Smart Technology and Artificial Intelligence to health care is driving exciting developments and transforming the sector. It has considerably advanced our ability to expand surveillance of disease and death and to store, manage and analyse vast amounts of patient and socio-economic data. It has also facilitated the development of new diagnostic tools and personalised medicines. These technologies promise to advance public health and revolutionise the targeting and monitoring of access to healthcare. At the same time, the presence of tech giants in this sector and the increase of public-private data sharing could potentially enhance inequalities in health care provision. This is contrary to human rights “right to health” legislation.
The right to health is recognised under Article 25 of the 1948 Universal Declaration of Human Rights. This provides that everyone, irrespective of where they are born, or of their sex, religion, or any other individual characteristic, has an entitlement to the facilities, goods, services, and conditions necessary to attain the highest attainable standard of physical and mental health. This is not a right to be healthy, but a right to receive the maximum standard of care available to everyone else. It includes maternal, child, and reproductive health services, healthy workplaces and safe environments. It includes the prevention, treatment, and control of diseases, and access to essential medicines as well as safe and drinkable water and sanitation.
Under the terms of the legislation, governments are the primary human rights ‘duty bearers’. This means they have obligations to respect, protect and fulfil people’s right to health. Governments have a duty to ensure that health care is provided on a non-discriminatory basis, and that access to good quality care, provided in a culturally acceptable way, is continually improving.
Through the application of Big Data, it is possible to identify and understand how, when and why a population is accessing healthcare services or whether they are being denied. It is also possible to track the mean and distribution of health outcomes. Being able to measure and monitor access and outcomes is essential to fulfilling right to health obligations.
One form of Big Data is administrative data. This refers to the data sets compiled from government agencies. These data sets contain information for the entire population rather than for samples, as is typically the case with survey data. This may include all the data coming from the tax agency, the Census, justice, health, education, transport, immigration, and so on. These data sets have the advantages of size (useful for statistical analysis and for the disaggregations necessary to evaluate inequalities in access and outcomes), and of representativeness (no group is excluded). There are increasing opportunities to link these data (after anonymization procedures) across domain-specific registers and to geocode the data to study neighbourhood blocks or catchment areas within a country. For example, neighbourhoods experiencing the greatest hardships can be identified, and their access to the services monitored. Or we can identify discontinuities in access and outcomes across catchment area borders.
Big Data can help identify discrimination. For example, in the location of facilities, or associated with language barriers, lack of awareness of available services, clinic opening hours, or fees for health services or medicines. Once access issues are identified, governments have the information needed to address the barriers to universal access.
An important human rights principle is that inequities in health must be reduced. Governments can be held to account where disadvantaged groups, who are not able to access health care, fall behind in terms of health outcomes. Only by improving access to quality health care for those with the worst health can inequities in health be reduced.
Governments have to report on their human rights duties to various United Nations bodies. The granular reports generated by Big Data can identify where discrimination exists, and the likely causes of it. This can help governments address the rights to health (and other human rights) of least advantaged people. Each time a government reports it must demonstrate that it has attempted to reduce the inequities identified previously. This is part of their human rights obligation to progressively realise the right to health.
As a result of new technologies, the health care, public health, and preventive health landscape is changing. The range of big data driven health care services include personalised medicine, especially designed to provide treatment for an individual (based on genome sequencing, data and informatics, and even data from wearable technology, such as fitness trackers).
Big data is accumulated from multiple sets of data including DNA sequencing, forensic, genetic, or medical databases, data from public health studies and clinical or drug trials, imaging data (for example, MRIs). Personal information is also available from health records, fitness and tracking devices, online activities, and spending. All of these can be re-purposed for various technical inventions. These large data sets are driving the burgeoning Artificial Intelligence industry in health care. Where available and accessible these technologies offer improved public health, clinical care, and patient management. This will mean improved and more effective treatment options, greater efficiency with diagnosis, treatment and follow on care. It is claimed, with little evidence, AI can make health care less expensive.
Increasingly, tech giants like Facebook and Google are expanding into the healthcare sector, capitalising on their experience collecting and mining Big Data to develop new data-driven technologies.
By partnering with resource-scarce public health institutions like the NHS, these companies hold the promise of advancing the right to health by improving clinical efficiency, the quality of healthcare and access to health services. However, the involvement of private corporations in developing these new tools may present a number of significant and, thus far, under-explored risks to the right to health. For example, partnerships could allow corporates to extract disproportionately high profits from public data sets without fairly compensating the NHS. This could further cement a potentially monopolistic position in the data-driven economy. Growing power asymmetries between the tech giants- who have the opportunity to exert an increasingly strong influence on policy making and research in health- and everyday citizens pose a significant challenge for human rights accountability and calls into question the limited protection afforded by the Ruggie Principles.
We examine Big Data through a right to health lens and identify both opportunities and threats to the right to health and health equity in a new data-driven economy. We demonstrate the use of comprehensive big data sets for assessment of the success of universal health coverage, the role of state-led judicial accountability for health provision, and the evaluation of recent policy initiatives influencing violence against women and abortion. We recommend that governments carry out human rights impact assessments before embarking on the use of Big Data in the health sector just as they should prior to adopting and implementing policies in other domains.
Our research also maps the right to health implications of data-sharing partnerships in the UK through emerging DeepMind Health NHS partnerships. Drawing on literature from the political economy, sociology and human rights law, it explores how data sharing between the NHS and technology companies may facilitate the growing economic and political ascendancy of today’s tech monopolies and reflects on the implications of this for the right to health.