Precision medicine and data sharing
Precision medicine is an emerging field that uses biological (including genomic), medical, behavioural and environmental information about a population to provide more specific and tailored healthcare (sometimes called personalised medicine). Precision medicine is expected to deliver significant gains in health treatments and outcomes and be a powerful tool for doctors and their patients. PM research requires large amounts of genomic and clinical data from diverse populations in order to make robust and reliable observations about health and disease. Broad public participation is essential to the generation of these large datasets. Community buy-in will depend on widespread trust and social license, which means that data sharing practices must broadly align with public expectations. Most PM programs will find it impracticable to ask for individuals consent each time data is used or shared. While studies suggest broad support for sharing PM data with researchers at publicly funded institutions, there is reluctance to share health information with private industry for research and development. As the private sector is likely to play an important role in generating public benefits from PM initiatives, it is important to understand what the concerns are and how they might be mitigated.
What is social license?
It is important to understand they public’s expectations, goals and concerns with respect to large population level health datasets. Social license refers to public acceptance of a particular activity or practice; it is not an explicit consent or legal permit, but instead a type of implicit social permission that is based on community approval and trust. Prior research has shown that people are often unaware of the extent to which their health and other administrative data is shared, linked and used, or the governance and regulatory measures that are put in place to facilitate sharing(Ballantyne, 2018; Ipsos MORI, 2016). Data sharing with diverse parties can be challenging because it requires balancing different, and sometimes competing, ethical considerations, including privacy, individual control and consent, trust, accountability and public benefit. It is therefore important to try to understand the limits of the social license in specific communities for certain data sharing activities. Studies conducted internationally have shown general support for sharing health data with researchers at publicly-funded institutions, provided that certain conditions are met, and most notably, high levels of data security and demonstration that the public interest is served by the data sharing arrangement (Hill et al., 2013; Kalkman et al., 2019; Stockdale et al., 2019; Garrison et al., 2015).
What is a citizens’ jury?
A citizens’ jury is a democratic process that supports citizens to understand the range of issues and different perspectives associated with a contentious topic. Citizens’ juries aim to develop recommendations for government, government agencies, and public and private organisations. The deliberation process requires the jury to help define the issue or problem, understand the context, generate ideas, analyse options and offer advice and recommendations. This is a well-established method of qualitative research and deliberative democracy, with clear process and procedures to ensure robust outputs.
What did we do?
We recruited 19 jurors and asked them to consider the question: Under what circumstances, if any, is it permissible for a national precision medicine program to share data with private industry for research and development? We focused on data sharing with private industry because this issue was identified by key stakeholders in Singapore, and in prior empirical research, as one of the most contentious elements of data-sharing for PM programs. The jurors meet over 4 days between December 2020 and April 2021. 15 jurors were present for the final day of deliberations. The citizens’ jury was supported by an advisory panel consisting of key stakeholders including the Singapore Ministry of Health and/or others were involved in the National Precision Medicine Program. The jury heard from, and were able to engage with, academic and industry experts from Singapore and overseas.
What did we find?
The jury expressed conditional support for sharing Singaporean precision medicine data with private industry for research and development; under some specific conditions. Overall, the jury agreed that PM data could be shared with pharmaceutical, biotechnology and technology industries, but not the private life/health insurance industry. The jury took this position based on their assessment of the balance between potential benefits to Singaporeans and potential harms. The benefits they found particularly compelling were new medical knowledge and interventions (especially for Asian populations), benefiting future generations, economic development and strengthening of the R&D sector in Singapore; while the relevant harms were unfair profiteering from Singaporean data, data misuse leading to stigma or harm, particularly in relation to companies overseas operating outside Singapore’s legal jurisdiction. Despite existing regulatory and policy protections, the jury remained concerned about the potential harms arising from sharing PM data with private industry, and in particular with private insurers, especially the risk of discrimination. The jury specified three assumptions and nine recommendations. The assumptions were taken to reflect existing consensus about how PM will be conducted in Singapore.
Assumptions:
A1. Data shared with private companies should be de-identified.
A2. People need to opt-in to PM and have the right to withdraw at any time.
A3. When people consent to the PM program, information should be comprehensible. For example, they should have someone to talk to, not relying on long written consent forms with lots of terms and conditions that people do not read.
The jury produced the following 9 recommendations for data sharing with private companies. All of these were unanimously endorsed by the 15 jurors present on the final day.
1. All data sharing with private industry should be in the public interests of Singaporeans. This means there is public benefit for Singapore. Private companies should not be able to access PM data solely for commercial or business purposes. |
2. We should not share data with insurance companies before there is anti-discrimination law in Singapore to prevent genetic discrimination for life and health insurance. |
3. We should establish an inter-agency committee to approve applications of PM data sharing with private industry; and this should include broad representation from agencies, for example: MOH, HSA, EDB, MOL; and community representatives. |
4. The oversight committee should consider the consequences of data sharing with respect to fairness and relative financial disadvantage between Singaporeans. e.g. cost of medicine in the future, some people not being unfairly discriminated against in insurance. |
5. There must be an accreditation process to ensure that private companies receiving the data are competent, reputable and trustworthy, and there should be enforceable contractual mechanisms in place to ensure overseas companies can be held accountable for any breach or data misuse. |
6. If companies breach the terms of the data access contract, they should be held accountable based on the severity of the breach; and the penalties should include the loss of access to the PM data for a number of years, fines, and criminal charges. |
7. Organizations, teams and individuals should be held accountable for data misuse at both the companies receiving the data and the public agency(s) responsible for releasing the data. |
8. The following should be made publicly transparent: the process of decision-making about sharing PM data with private industry; the companies who have accessed the data and their purpose in accessing the data; a summary of the research outputs so the public can judge the benefit of data sharing; and when there is a data breach and/or what penalties are issued. |
9. There should be higher levels of restrictions for sharing more sensitive data. |
Are these findings different from previous research?
Our results aligns with prior international studies which found conditional acceptance for data sharing with private industry, a public benefit requirement, specific reluctance to share with insurance companies, and an emphasis on accountability and transparency in order that data holders and users can demonstrate trustworthiness. However, our results differ from prior studies in that individual consent did not dominate the deliberations; jurors were able to set it aside as an assumed prerequisite for participation in a precision medicine program as a whole and subsequently were not specifically concerned about individual consent for each time data was shared with a new user.
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Garrison NA, Sathe NA, Antommaria AH, et al. (2015) A systematic literature review of individuals' perspectives on broad consent and data sharing in the United States. Genetics in Medicine 7(18): 663-671.
Hill EM, Turner EL, Martin RM, et al. (2013) "Let's get the best quality research we can": public awareness and acceptance of consent to use existing data in health research: a systematic and qualitative study. BMC Medical Research Methodology. DOI: 10.1186/1471-2288-13-72.(13): 72.
Ipsos MORI (2016) The One‐Way Mirror: public attitudes to commercial access to health data. Available at: https://www.ipsos.com/sites/default/files/publication/5200-03/sri-wellcome-trust-commercial-access-to-health-data.pdf (accessed November 11, 2021).
Kalkman S, van Delden J, Banerjee A, et al. (2019) Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. Journal of Medical Ethics. DOI: 10.1136/medethics-2019-105651. 3-13.
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