Sharing precision medicine data with private industry: Outcomes of a citizens’ jury in Singapore

Abstract

Precision medicine is an emerging approach to treatment and disease prevention that relies on linkages between very large datasets of health information that is shared amongst researchers and health professionals. While studies suggest broad support for sharing precision medicine 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 precision medicine initiatives, it is important to understand what the concerns are and how they might be mitigated. This study reports outcomes of a deliberative method of citizen engagement in Singapore that asked whether sharing precision medicine data with private industry would be permissible, and if so, under what circumstances. Findings from this citizens’ jury suggest sharing with industry would be permissible under certain conditions that are set out in nine recommendations. Implications of the recommendations and their underlying assumptions for policy decision makers are discussed. This study 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 to demonstrate trustworthiness. However, our results differ from prior studies in that opt-in consent did not dominate the deliberations as jurors were able to set it aside as an assumed prerequisite for participation in a precision medicine programme.

Keywords

Precision medicine citizens’ jury public deliberation health data private commercial

Introduction

Precision medicine (PM) is an emerging approach to treatment and disease prevention. It links genomic (and other omics) data with medical, behavioural and environmental information about patient populations to more accurately stratify subgroups and provide tailored care to individuals. PM represents an incremental shift towards more data-heavy personalization in research and healthcare (Schaefer et al., 2019).

More than 40 countries, including the United States (USA) (National Institute of Health, 2020), United Kingdom (UK) (The Lancet, 2018) and China (Sanders and Oberst, 2016), are investing in PM initiatives. However, the genomes of Asian populations remain under-represented in international databases used in PM. In 2020, the National Precision Medicine (NPM) Steering Committee (Ipsos MORI, 2016) in Singapore completed the first phase proof-of-concept studies. These included the sequencing of 10,000 individuals who had participated in cohort studies led by multiple academic centres and public health institutions (Wu et al., 2019). The Ministry of Health has subsequently launched a central agency called Precision Health Research Singapore (PRECISE, 2021) to oversee the whole-of-government implementation of the next phase of the NPM strategy.

PM research requires large amounts of genomic and clinical data from diverse populations in order to make robust observations and avoid drawing conclusions from associations that occur due to chance or unrepresentativeness and, thereby, biased datasets. Community buy-in and participation are essential to the generation of these large datasets and will depend on widespread trust and social license, which means that data sharing practices must broadly align with public expectations (Master et al., 2015; Carter et al., 2015). Yet, 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 (Sankar and Parker, 2017; Chataway et al., 2012). 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).

However, this support tends to decrease when private companies have access to the data and when public sector health data is used for commercial gain (Xafis, 2015; Ipsos MORI, 2016; Aitken et al., 2016; Dive et al., 2020). Research in the USA and the UK found that the more commercial the purpose of the receiving institution (such as an insurance or tech company), the less willing respondents were to share anonymised personal health information (Ghafur et al., 2020). This presents a challenge for PM research, which often involves partnerships between academic centres and commercial entities. Commercial companies can provide funding to carry out the research. They can also offer the necessary skills and infrastructure to develop scientific insights derived from PM into products, and then produce and market them at scale to maximize the health impacts of research (Wang et al., 2016).

To examine community expectations of data sharing with commercial entities as part of PM, we convened a citizens’ jury in Singapore. Theoretical work on deliberative democracy has prompted a range of methods for convening ‘mini-publics’ to deliberate on contested public policy issues (Street et al., 2014). Taking different forms, and referred to by different terms (e.g. citizens’ jury, community jury) (Tully et al., 2019; Smith and Wales, 2000; Degeling, 2019) these mini-publics have the following characteristics: (1) a group of people selected randomly or purposively who act as a ‘mini public’ – this group is designed to be inclusive of the diversity in a larger group (e.g. all affected people, all members of a community or all residents in a country); (2) provision of good quality information to support informed decision making; (3) appropriate conditions and sufficient time and opportunity to discuss issues and work together to come to a reasoned set of conclusions (Degeling, 2019).

Citizens’ juries are designed to produce normative findings to guide public policy. That is to say, the jurors themselves are undertaking informed normative reflection and analysis (‘deliberation’) on the prescribed question. As a result of the depth and nuance made possible by the jury format, their recommendations can directly inform policymakers; the study team commits to communicating the jurors’ recommendations, as given, to outside audiences. However, there is scope for additional analysis of the jury findings, primarily aimed at clarifying and contextualizing the jury‘s recommendations, as well as elaborating on the apparent implications of those recommendations for policy.

Several countries have conducted citizens’ juries to explore public concerns about sharing health data with commercial companies. A recent citizens’ jury in the UK on the commercial use of health data found that private profits were acceptable so long as the public benefit was delivered. (Fiore and Goodman, 2016) Juries in Australia found citizens objected to their data being used in ways that do not produce public goods, for example, sharing with commercial entities to generate profits (Degeling et al., 2020). In another study, Australian citizens were willing to accept sharing their health data, including with private industry, providing the intended purpose was clearly of public benefit, sharing occurred responsibly in a framework of accountability and the data were securely held. In contrast to the previous study, the jurors did not explicitly reject profit generation (Street et al., 2021). While the methodologies for these studies would have varied slightly, it is likely that any differences in findings will reflect different cultural and social values. If this assumption is correct, then results from Australia and the UK should not be assumed to automatically apply to other regions or countries. Previous empirical research conducted in Singapore suggests an openness to allowing data sharing with the private sector but only under certain circumstances (Lysaght et al., 2021). Hence, we convened a citizens’ jury to better understand what conditions would apply to PM data sharing in Singapore.

Methods

The methods here are reported in line with the CJ Check checklist for reporting community juries (Thomas, 2016). We focused on data sharing with private industry because this issue was identified by key stakeholders in Singapore, and in prior empirical research (Lysaght et al., 2020) as one of the most contentious elements of data sharing for PM programmes. Our citizens’ jury asked participants to consider the question: Under what circumstances, if any, is it permissible for a NPM program to share data with private industry for research and development?

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 NPM. The advisory panel played an integral role in shaping the question (or ‘charge’) put to the jury and provided broad-ranging advice on the scope and conduct of the event, including the expert topics covered, and recommending expert presenters and stakeholder representatives. In addition to the advisory panel, a group of Australian academics (AJN, SC, CD, ABM) with expertise and experience in deliberative research methodologies provided advice on the jury methodology and findings throughout. Our citizens’ jury was based on methods and resources used in a similar Australian citizens’ jury on data sharing with the private sector (Street et al., 2021).

We obtained an ethics review exemption to conduct this research from the National University of Singapore – Institutional Review Board (NUS-IRB). The jury process conformed to the social distancing and public health restrictions imposed during the 2020 pandemic including masks, limits on people per room and per table.

A professional market research firm (Projective Insights Consultants) drew from their proprietary panel¹ using purposive sampling to recruit a jury that was broadly inclusive of Singapore‘s ethnically diverse population. The inclusion criteria included Singapore Citizens or Permanent Residents between 21 and 65² years who were fluent in English and available for the full three days scheduled in December 2020. Jurors were not expected to have any personal experience with PM or commercial data sharing. Candidates who had prior work experience in the past 5 years in PM, pharmaceutical or biotech companies, genomics or technology companies using health data were excluded. Because deliberative methods assume that participants are willing to consider reasons given by others, and to revise their own positions, people holding intractable views on political issues or the Singapore government³ were excluded. Jurors were selected for diversity in demographics including age, gender, ethnicity, income and education (see Table 1 for demographic information).

Table 1.

Jury characteristics.

Characteristics	No. of jurors
	Day 1	Days 2 and 3	Day 4
	(N = 19)	(N = 18)	(N = 15)
Age group (in years)
21–30	4 (21%)	3 (17%)	2 (13%)
31–40	4 (21%)	4 (22%)	4 (27%)
41–50	5 (26%)	5 (28%)	3 (20%)
51–60	4 (21%)	4 (22%)	4 (27%)
61–65	2 (11%)	2 (11%)	2 (13%)
Gender
Male	8 (42%)	8 (45%)	7 (47%)
Female	11 (58%)	10 (55%)	8 (53%)
Ethnicity
Chinese	11 (58%)	10 (56%)	10 (67%)
Malay	5 (26%)	5 (28%)	3 (20%)
Indian	2 (11%)	2 (11%)	1 (7%)
Others	1 (5%)	1 (6%)	1 (7%)
Highest education level
GCE ‘O’ levels	4 (21%)	4 (22%)	2 (13%)
GCE ‘A’ levels	1 (5%)	1 (6%)	1 (7%)
Diploma	7 (37%)	6 (33%)	5 (33%)
Bachelor's degree	7 (37%)	7 (39%)	7 (47%)

The jury was held in a Singapore hotel over three days in December 2020; and re-convened for the fourth day in April 2021. Nineteen jurors were recruited and present for days 1 and 2 with one withdrawing on day 3 for personal reasons. This size is standard for a citizens’ jury or deliberative democratic project where the purpose is to allow highly informed participants to deliberate deeply on an issue with support and time to engage with the topic. Citizens’ juries do not aim to be statistically representative (Karpowitz and Raphael, 2016): they aim to be inclusive and ‘descriptively representative of the community’ or ‘provide a cross-section of community perspectives’ (Karpowitz and Raphael, 2016). Fifteen jurors returned for day 4, which remained within the 12–25 participant range typical for citizen juries (Street et al., 2014).

Jurors were sent a handbook to read and some short videos to view prior to the jury (see Supplementary material S1). The jury was convened by two professional facilitators, one with local qualitative and market research experience and another with international experience in data governance and public policy development. The jury was supported by a four-member research team (AB, TL, HJT, SO) from the National University of Singapore who attended each day and answered questions; two (AB, TL) of whom also presented expert testimony. Jurors were reimbursed for travel expenses and paid SGD$150 per day (including day 4) plus another SGD$250 for completing the first three days.

On days 1 and 2, jurors were presented with video recorded expert testimony⁴ (10–15 min each) from academics in Singapore and Australia on the following topics: PM, privacy and data security, public–private partnerships, prior research in Singapore on data sharing, regulation, trust and ethical analysis (see Supplementary material S2 for full schedule). Jurors were informed about the relevant legislation that would apply to the collection, storage and use of PM data for research – Personal Data Protection Act (PDPA) and Human Biomedical Research Act (HBRA) – and the absence of laws to protect genetic information nondiscrimination (see Supplementary material S3 for more details). Experts were available for 15 min of Q&A either in person or via Zoom and additional questions were emailed to experts over the course of the jury. On day 2 the jurors, with the help of the facilitators, identified and agreed on four key areas for discussion: consent (what are the options?); access (who should have access and how?); public benefit (what counts?); and regulation (what do we need?). Jurors also had the opportunity to discuss the charge in small groups with key industry stakeholders working in the following fields: pharmaceutical/biotech, private insurance, clinical research, privacy law and economic development.

On day 3, each of the four working groups proposed recommendations. The jury determined by consensus the supermajority required for a recommendation to be accepted: this was set at 75% (14/18) of all jurors. On day 3, the jury also voted in favour of 29 initial recommendations and rejected four. Jurors were able to abstain from voting, but this did not alter the denominator (i.e. 18) for the required supermajority.

The significant gap between days 3 and 4 gave jurors time to reflect on the issues away from the group, undertake independent research and consult with their communities. During this period, jurors individually completed an online prioritization exercise where they selected the most important of the 29 recommendations and provided reasons for their choice (see Supplementary material S4 for results of this exercise). The research team qualitatively analysed data from the first three days of deliberation and prepared a preliminary report on progress and interim findings. This report was shared with jurors in order to check the accuracy of the research team‘s interpretations of the deliberations (Birt et al., 2016) and was provided to the advisory panel and the team of external Australian experts to identify any specific issues that needed clarification.

Day 4 was an important opportunity to refine and focus the recommendations. On the day, they were also informed about a moratorium between the Singapore Ministry of Health and the Life Insurance Association that had been introduced on day 3 to prohibit the use of individuals’ genetic test results in insurance underwriting (Ministry of Health, 2021b). Throughout the day, the jury prioritized the 29 recommendations by perceived importance, considered implementation challenges, resolved potential tensions between recommendations, and refined the wording of the recommendations. This process produced nine final recommendations based on three overarching assumptions. The jury also noted six additional suggestions that are not presented with the recommendations but are accessible in the Supplementary material (see S5).

In addition to field notes taken over the four days, the jury sessions were audio-recorded, transcribed and jointly coded by the research team (AB, TL, HJT, SO). Jurors individually completed a Likert scale survey measuring views about data sharing and trust at five different time points and an evaluation (see Supplementary material S6 for results).

Results

Overall, the jury agreed that personal 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. We detail the assumptions underlying this position, and the jury’s more detailed recommendations, below.

Overarching assumptions

The jury specified three assumptions that the recommendations below rest upon. The assumptions were taken to reflect the existing consensus about how PM will be conducted in Singapore. Failure to satisfy these base conditions could de-legitimize the jury’s recommendations.

A1. Data shared with private companies should be de-identified.

The jury recognized that data could not be effectively anonymized and that there were degrees of de-identification and different strategies for protecting data. They accepted expert testimony that PM governance structures in Singapore would not permit the sharing of identifiable data with researchers in accordance with the PDPA.

A2. People need to opt-in to PM and have the right to withdraw at any time.

The jury understood that all participants in PM cohorts would have actively volunteered and clinical or genomic data would not be passively collected for PM research. The jury accepted that some version of broad consent would be used at the point of entry into a PM cohort and this would cover, in general terms, potential uses and users of the data. Some jurors endorsed the idea of a time-limited broad consent that would expire after 5–10 years, given that the data ecosystem is changing so rapidly.

While recognizing the complexity of operationalizing withdrawal in the context of data studies, the jury assumed, based on expert testimony, that when an individual withdraws from PM programmes, their data would be deleted from the dataset and would not be shared with any future research studies. The jury acknowledged that PM data, which had already been shared with researchers, could not subsequently be extracted from previous or current studies.

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 felt that consent in relation to healthcare should be genuinely informed, and contrasted this against consent obtained, for example, with apps and online services. They perceived an important difference between signing a consent form, or accepting online terms and conditions, and substantively understanding the nature of the service or proposal. They expected PM programme managers to use proven communication strategies to ensure that people volunteering for PM research understood how their data would be shared and used.

Recommendations

Building on the three overarching assumptions outlined above, the jury proposed a further nine recommendations for sharing PM data with private industry (Table 2). These recommendations represent the jury’s normative conclusions regarding sharing PM data with private industry and are intended to guide public policy. The assumptions above describe components of the data sharing ecosystem that jurors expected were already established. In contrast, the recommendations below outline conditions or requirements that the jury believed should be incorporated into the governance of PM data in Singapore because they were not perceived as being adequately established in standard practice, policy or the law.

All data sharing with private industry should be in the public interest 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.

Table 2.

Jury report: Recommendations and reasons.

It is permissible for a national precision medicine (NPM) programme to share data with private industry for R&D under some circumstances
RecommendationsUnanimously endorsed by the 15 jurors on the final round of voting.	Reasons	Imputed valuesJurors drew on these values in support of this recommendation
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.	This recommendation received relatively little debate and there was consensus on this point from early in the deliberations. Private profit was seen as acceptable, but only where there was sufficient public benefit derived from data sharing (a ‘win-win’ scenario). Some jurors made ownerships claims regarding the data to justify entitlement to the benefit of PM research.	Public interest Public benefit Public good Ownership Nationalism
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.	Jurors wanted to promote well-being, access to healthcare and equity within Singapore; and prevent discrimination due to higher insurance premiums for high-risk groups and potential exclusion from insurance coverage.	Anti-discrimination Harm minimization Fairness Equity Well-being Charity Public interest
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.	This committee would operate in addition to IRB approval (where necessary) and would assess individual applications for sharing with private companies according to any relevant law or regulations and the substantive recommendations presented here. Members should represent diverse perspectives within Singaporean. Approved data sharing projects should be relevant and beneficial to Singapore.	Public interest Equity Trust Accountability Expertise Risk minimization
4. The oversight committee should consider the consequences of data sharing with respect to fairness and relative financial disadvantage between Singaporeans. For example, cost of medicine in the future, some people not being unfairly discriminated against in insurance.	The jury was concerned that the benefits of data sharing would not be fairly distributed within Singapore and some groups would benefit from new interventions but other groups may be financially disadvantaged, unable to afford expensive medical interventions, uninsured or stigmatized. Equity, inequality and fairness were important and persistent concerns for the jury.	Equity, Inequality Fairness Harm minimization Well-being Charity Public interest Anti-discrimination
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.	Jurors saw the potential value in sharing data with companies outside Singapore and wanted to allow collaboration. Strong accountability and enforcement measures were seen as a necessary prerequisite for sharing data internationally. Appropriate accreditation of private companies would help minimise the risk of data misuse and promote public trust	Accountability Risk management Harm minimization Trust Utility (accessibility of data) Control Public interest
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.	Accountability for data was a priority concern for the jury. They wanted a variety of punitive measures that would punish and deter data misuse.	Accountability Risk minimization Deterrence Retributive Justice Responsibility Proportionality
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.	The jury wanted actual people to be held accountable for data breaches and/or data misuse. They wanted people at both the public agency and the private company to take responsibility and be penalized if data security is breach or data is misused.	Accountability Fairness Responsibility Risk minimization Deterrence (prevent negligence) Retributive Justice
8. The following should be made publically 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.	There was sustained support for transparency throughout the deliberations. Jurors believed that transparency could help inform the public, promote trust, and allows the public to judge the benefits of PM for themselves. Some jurors conceived of data of as public property arguing that Singaporeans are entitled to know how it is shared.	Transparency Public interest Trust Ownership Autonomy (informed decision making about the benefits of PM)
9. There should be higher levels of restrictions for sharing more sensitive data.	Jurors wanted proportionally regulation that relates to the risk of data sharing. The jury did not agree on a definition of sensitive data, but examples include HIV patients, or psychological or psychiatric conditions, genomic data, raw and individual level data.	Proportionality Risk minimization Privacy Control Harm minimization

PM, precision medicine.

This recommendation received relatively little debate or refinement, as there was consensus on this point from early in the deliberation. The jury expressed concern about the potential for private companies to profiteer from Singaporean data, by which they meant deriving profit without producing sufficient public benefit for Singaporeans or humanity more generally. Examples of public benefits cited by jurors include targeted and accurate treatment, medical innovation, fewer adverse events, cheaper medicines, increased longevity and better quality of life, more efficient use of medical resources, improved understanding of the health of Asian populations, improving the quality of life of future generations, treatments for rare diseases, strengthening the research and development sector in Singapore, and job creation.

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.

Sharing data with private insurance was a particularly contentious element during the deliberations and the jury held significant concerns about sharing PM data with insurers. This recommendation followed discussions with an industry representative on day 2 who put forward the potential benefits for sharing PM data with private insurers. The representative strongly made the case that access to PM data may allow the development of more sophisticated models to stratify patients according to risk, which could result in lower premiums for low-risk groups; and that data accessed from PM programmes would not be used to assess or evaluate individuals applying for insurance coverage as they would not contain personal identifiers. Nonetheless, jurors remained concerned about the cost of health insurance⁵ (Cindy, 2021; Tan et al., 2021) and the threat of genetic discrimination.

While citizens and permanent residents are entitled to government health insurance (Ministry of Health, 2021a) the coverage is basic and many people buy additional private insurance. On day 4, we presented information to the jury about a recently signed moratorium between the Singapore Ministry of Health and the Life Insurance Association which prohibited the use of individuals’ genetic test results in insurance underwriting. (This Mortarium was agreed upon in the period between day 3 and day 4). Jurors did not believe the moratorium alone would offer sufficient protection against discrimination in private health and life insurance based on applicants’ genetic tests, and therefore required antidiscrimination legislation. Jurors hoped that legislation would promote fairness and equity, as well as prevent discrimination due to higher insurance premiums for high-risk groups and potential exclusion from insurance coverage.

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: Ministry of Health, Health Sciences Authority, Economic Development Board, Ministry of Law; and community representatives.

This committee would operate in addition to IRB approval (where necessary) and would assess individual applications for sharing with private companies according to the other substantive recommendations. Members of this committee should have relevant expertise and represent the diverse perspectives of Singaporeans. PM data was seen by some jurors as public property or a national resource and this Committee would be responsible for deciding how to manage and govern this resource. Though jurors were not particular about terminology, this recommendation bears some similarity to a data access committee, albeit one composed of multiple government agencies.(Cheah and Piasecki, 2020)

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, people being unfairly discriminated against in insurance.

Equity, inequality and fairness were important and persistent concerns for the jury. Jurors were concerned about the high costs of health care in Singapore, rising economic inequality and unequal access. The jury was enthusiastic about the potential for private industry to use PM data to drive innovation and develop new medicines, tests and other health interventions; but were concerned that these products and services would be unaffordable to some Singaporeans and could contribute to health inequality. Jurors wanted the oversight committee to consider, to the extent possible, the social justice implications (such as equity, caring for the most vulnerable, preventing discrimination) when considering applications from private companies to access PM data.

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.

Strong accountability and enforcement measures were seen as a prerequisite for data sharing, especially when sharing internationally. Jurors were more concerned about data misuse by people with legal permission to access the data, rather than the risk of data being hacked by unauthorized users. Appropriate accreditation of private companies would help reduce the risk of data misuse. The second part of this recommendation relates to sharing data with companies based outside of Singapore. Initially, the jury preferred to restrict access to private companies based or registered in Singapore because this would create local jobs and ensure Singapore data protection and research laws and regulation would be enforceable. On balance, the jury decided this might unnecessarily restrict the number of companies who could assess PM data, but they wanted to see contract law used to ensure that overseas companies could be held accountable.

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.

Emphasizing the importance of accountability, the jury wanted a variety of punitive measures that would deter data misuse. The jury thought that fines alone may not sufficiently penalize multinational companies and wanted to see companies lose access to the data or face criminal charges for serious data breaches or misuse. This recommendation aligns with the findings of the survey administered throughout the jury, where jurors indicated the most important condition for sharing data with a private company was criminal penalties or heavy fines if companies break the rules.

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.

The jury wanted identifiable individuals to be held accountable for data breaches and/or data misuse. This measure applied to staff working at any public agency responsible for managing and releasing the data as well as private companies. Some jurors were concerned that agencies and individuals had not taken sufficient responsibility for prior high-profile data breaches in Singapore (Ai-Lien et al., 2021; Mohan and Sim, 2019).

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.

Transparency was seen as an important platform for the public to be able to judge the benefits of PM data sharing with private industry and hold public agencies accountable. It was argued that Singaporeans are entitled to transparency because it is ‘their’ data being shared; and that transparency can help inform the public, promote trust and allow people to judge for themselves the benefits of PM and assess whether they are worth the risks. Recommendation 1 sets a public benefit imperative on data sharing with industry; the jury wanted a summary regarding the purpose of each project to be able to identify and judge whether this public benefit standard was met. The jury recognized that transparency may clash with a company’s interests; but did not think companies’ commercial interests should trump the public interest in transparency.

9. There should be higher levels of restrictions for sharing more sensitive data.

Jurors wanted proportionate regulation that relates to the risk of data sharing. The jury did not agree on a definition of sensitive data⁶, but examples included HIV status, or psychological or psychiatric conditions, whole genomic sequences, as well as raw and personally identifiable data. The jury recognized that, while only de-identified data would be shared with private companies, there are degrees of de-identification and data security, that the risk of reidentification cannot be eliminated, and that this risk is context dependent (e.g. contingent on how data are linked and what other information is publicly available). The jury also recognized the risk of family and group harm, where genomic research findings may be used to stigmatize or disadvantage groups/classes of people. The jurors expressed a tendency towards genetic exceptionalism; they afforded greater scrutiny to the sharing of genetic data than for other personal data including information about health and family history. Decisions to share data with private companies should therefore take into account the relative sensitivity of data, the risk of reidentification and the possibility of group harm.

Other observations

While there was general enthusiasm for the potential benefits of PM, there was also some skepticism about the effectiveness and accuracy of PM research. There was concern that over-reliance on genomic data could lead to misdiagnoses, an inability to see the patient as an individual, and an undermining of the doctor–patient relationship. As indicated in the survey results (Supplementary material S6), jurors thought all suggested conditions were important (5.2–6.6/7 on a Likert scale) and their responses were fairly consistent across the five times the survey was administered. The most important condition for sharing data with a private company was that there are criminal penalties or heavy fines if companies break the rules. Jurors expressed trust in a NPM programme to use data responsively, respond quickly to data breaches and be open and honest about how data is collected.

Despite the social distancing and public health restrictions imposed during the 2020 pandemic, the jury evaluation forms (see Supplementary material S7) and comments indicate that jurors felt engaged and stimulated and that the jury was enjoyable (4.9/5) and worthwhile (4.9/5) and that they would participate in similar events in the future (4.6/5).

Discussion

The outcomes of our citizens’ jury provide insight into the conditions under which sharing PM data with private companies in Singapore may be publicly acceptable. The jury did not discuss sharing PM data with the public sector or non-for-profit organizations should not be read as being directly applicable to sharing with those sectors. Our jury demonstrated support and enthusiasm for the potential benefits of PM for Singapore – in terms of improved knowledge about health and disease, as well as economic activity and strengthening of the research sector. Sharing with pharmaceutical, biotech and technology companies may be acceptable under the conditions described in the recommendations; but sharing with insurance companies would probably not be acceptable in the absence of anti-discrimination legislation. The primary normative outcome from the jury is represented by the final nine recommendations, which were endorsed unanimously (Table 2). Here we reflect on the jurors’ normative conclusions and how these align with or depart from existing literature about public perceptions of health data sharing. We also offer our own conceptual and normative analysis, drawing on the existing empirical and ethics literature on data sharing, to indicate how the jury’s recommendations might be translated into policy.

Our deliberative process found that accountability and public interests were the most important considerations for the jury. Jurors wanted robust governance and oversight processes to minimize the risks of negligence, data breaches and data misuse. There was a strong consensus that transparency, accountability and punitive measures were necessary to prevent data misuse, ensure fair recourse and maintain public trust in data sharing. Sharing with private companies was acceptable when such arrangements would generate public benefits for Singaporeans. The remaining areas of contention between jurors include the need for specific consent, charging companies to access the data, sharing data with companies overseas.

Our findings are consistent with studies internationally suggesting that public interest, accountability and transparency are critically important considerations for public support of data sharing. These values feature in the ethics and governance frameworks of internationally shared genomic datasets, such as UK biobank (UK Biobank, 2007), and in the empirically informed principles of ‘Medical Information Commons’ being developed for trustworthy data sharing in the USA (Cook-Deegan et al., 2019). The emphasis on accountability reflects ongoing concerns about the inadequacy of existing legal protections for participants in genome data sharing programmes, including PM (Hammack et al., 2019). However, scholars have cautioned against proposals for greater criminal sanctions and legal redress on grounds that they are disproportionately punitive and may negatively affect data sharing initiatives, even where there is a potential public benefit (Phillips et al., 2017).

Singapore has a reputation for a strict judicial system and rigorous law enforcement resulting in low crime rates (U.S Department of State, 2020). Existing data protection and research legislation (PDPA and HBRA) entail criminal penalties, for example, the penalties that ensue when there is a failure to gain informed consent (see Supplementary material S3). Under HBRA individuals may be held accountable; however, liability is corporatized under the PDPA. Perhaps unsurprisingly then, accountability was critically important to the jury: in the survey, jurors indicated that the most important conditions for data sharing with private companies were the existence of criminal penalties or heavy fines if companies breach the rules, and the recommendations include call for criminal penalties and individual professional responsibility for data misuse and breaches.

In contrast with much of the international literature, none of the jury’s final recommendations related to consent. Existing literature on public attitudes to health data sharing assumes that different consent models will be highly influential in public participation in biobanking and data sharing (Sankar and Parker, 2017; Fiore and Goodman, 2016). Consent was a dominant issue early in the jury process, when a requirement for valid opt-in consent and an opportunity to discuss participation (rather than just complete a form), and the right to withdraw, were described as necessary conditions for PM programmes. There was not an extended debate about the quality or specificity of consent models or options (e.g. broad vs. specific consent), and consent was progressively de-prioritized over the course of the deliberations.

Prior qualitative research (Lysaght et al., 2020) and a recent survey of Singaporean’s views about health data sharing (Lysaght et al., 2021), found that broad versus specific models of consent were less important to respondents than other considerations such as the use and users of the data: similar evaluations may also have informed the jury’s focus. The reasons for this de-emphasize on individual consent (for each instance of data sharing) will need to be explored in future research. Some scholars (Lemmens, 2016; Akpa-Inyang and Chima, 2021; Lee 2015) have suggested that a focus on different consent models derives from a Western-led atomistic concept of autonomy that dominates the liberal legal and bioethics literature, and may be less relevant in other cultural contexts (Chua, 2018). The jury’s conception of PM data as a public resource may make individual consent less apposite. Alternatively, it may be that those who design studies about data sharing start with the assumption that consent models are important and this is reflected in the research design.

Towards trustworthy governance for sharing of PM data with private industry

Demonstrating trustworthiness in the governance of health and administrative data is an essential task for governments (Department of Health and Social Care, 2018; Sheehan et al., 2020; Data Futures Partnership, 2017). Trust requires a leap of faith and depends on judgment about both the competence and values of the institution in question. There is academic debate about the extent to which cultivating trust in societal institutions requires transparency, openness and accountability – do these demonstrate trustworthiness or simply show we are not prepared to take the leap of faith that trust requires? (O’Neill, 2002; Sheehan M et al. 2020) The jury’s recommendations imply that accountability and transparency were necessary to cultivate trust in PM data sharing in Singapore.

Because public trust and acceptance are prerequisites for broad participation in PM programmes, countries with higher trust and willingness to share data with different sectors may reap greater benefits from PM endeavours. Recent empirical research suggests that countries with heavily privatized health systems (such as the USA) may be associated with greater public reluctance to share health data for research and greater distrust, particularly of commercial end users of data compared to countries with a socialized single-payer system (such as the UK) (Ghafur et al. 2020). Singapore has a substantial private healthcare sector, but the system is predominantly government-run and publicly funded via tiered insurance schemes, that is Medisave, Medishield Life and Medifund (Tan et al. 2021). Indeed, survey research (Lysaght et al., 2021) correspondingly reported high levels of trust in Singapore hospitals and the health ministry with relatively less trust in private companies. Those findings suggest support for sharing PM data with private companies would be highly conditional.

Our jurors developed three priorities for maintaining public trust in a national PM programme and public support for data sharing with private companies. First, data should not be shared with the private insurance industry at this stage. Second, decision makers should ensure that data sharing arrangements offer a clear public benefit for Singaporeans, and that this is transparently communicated to the public. Third, decision makers should minimize the risk of data breaches and misuse by only sharing with reputable and competent companies, be open about errors when they happen, and ensure proportional punishments for negligence or data misuse.

It may be difficult to implement recommendation 4 which calls for the oversight committee to consider the consequences of data sharing with respect to fairness and relative financial disadvantage among Singaporeans. Review committees are typically not in a position to accurately predict future downstream consequences of research (Rogers and Ballantyne, 2009). However, those involved in the NPM should be attuned to the distribution of the benefits of PM and work towards achieving affordable healthcare for Singaporeans, addressing inequity and caring for the most vulnerable.

The recommendation of punitive actions against individuals for legal breaches, as a deterrent and mechanism to minimize risk, may also be difficult to implement. PM initiatives are complex programmes involving multiple sources and users of data, with different aims and values. Sheehan et al. have argued that ‘The larger and more complex the institution, the more uncertainty exists about how to understand its behaviour, and the more complex judgements of trust become.’ (Sheehan et al. 2020) This complexity was reflected in jurors’ efforts to fairly attribute accountability to both institutions and individuals within those institutions for data breaches or misuses. The strict judicial system in Singapore and social policies emphasizing personal responsibility has likely factored into our jury's recommendation for punitive action against individuals and not simply the corporations or institutions found to breach the law (Haskins, 2011) Another likely factor was some jurors’ beliefs that public officials and senior management had not been held to adequate account for previous high profile incursions (relevant cases included PricewaterhouseCoopers, 2019; Xiao and Zhou, 2020; Chesterman, 2014). However, accepted wisdom in organizational psychology suggests that risk management requires rapid reporting of errors and is easier to detect in a blame-minimizing workplace culture (Mcleod and Dolezel, 2018; Reason, 1997). Institutions with surprisingly low rates of accidents (e.g. air traffic control centres) – focus on patterns of error and system vulnerabilities rather than individual accountability for decision making (Reason, 2004). However, those involved in the NPM can consider how to implement the recommendation in ways that address the underlying value of accountability.

What are the strengths and limitations of the study?

Both public benefit and data sensitivity were important concepts for the jurors, as reflected in the recommendations. In the jury’s discussions, data sensitivity broadly referred to the idea that some types of personal data should be more protected because unauthorized access or disclosure could be especially harmful for data subjects, for example, data relating to mental health, sexual practice or stigmatized conditions. The jury offered a diverse range of examples for each term but did not agree on a precise definition of either concept. Singaporeans’ understanding of the public benefit and data sensitivity could be explored further in future work. Our selection criteria aimed to be broadly inclusive of the Singapore resident population although the small size of the jury and highly purposeful selection process limits the extent the results could be said to be representative of Singaporeans generally. It was also challenging to find stakeholders in Singapore who are strongly opposed to sharing publicly resourced health information with the private sector, which might have influenced the jurors’ deliberations although it is difficult to know if the recommendations would have been any different. In their feedback, jurors did not indicate that either the expert testimony or stakeholders’ interactions were biased and wanted to hear more about the reasons why PM data should not be shared with private industry at all.

The COVID-19 pandemic and associated social distancing and public health measures in Singapore influenced the conduct of the jury in various ways that limited social interaction and likely affected the dynamic of deliberation. All participants (jurors, experts and the research team) needed to keep 1 m distance, no more than five people could sit at a table, masks were worn at all times and hotel availability was significantly constrained, which led to splitting the jury over several months (December 2020–April 2021). Only 15 out of 18 jurors returned for day 4. However, a surprise benefit of this delay was the progression of the jurors’ reasoning between days 3 and 4, and the opportunity for the research team to prepare an interim report and share this with jurors, external collaborators and the advisory panel. In future, we will plan to schedule a break of several weeks before the final day of the jury.

What is the future of deliberative research on data sharing and in SG?

This was the first time a citizens’ jury following this methodology was conducted in Singapore and our results indicated it was successful. Our experience did not expose any substantial cultural barrier to open deliberation, discussion and consensus-building amongst participants. In our view, the two independent facilitators, including one with knowledge of local cultural norms and rapport building, were essential to this success. Application of pedagogical techniques, such as scaffolding to build the juror’s understanding of complex technical concepts, and to support an informed deliberation was also essential. Future policymaking around contested scientific and health issues in Singapore will benefit from this methodology.

Conclusion

This citizens’ jury in Singapore found that sharing PM data with private companies for research and development would be acceptable in certain circumstances. All data sharing had to be in the public interest of Singapore. The jury accepted that private companies could gain commercially so long as the public benefit was also proportionately achieved. The jury expressed specific concern about sharing PM with insurance companies, and they called for the introduction of anti-discrimination laws to prevent genetic discrimination for life and health insurance prior to sharing data with the insurance industry. The jury also required strengthened inter-agency governance and oversight structures, greater accountability for data breaches and harm, and increased transparency about both data sharing arrangements and decision-making process. This study 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 to demonstrate trustworthiness; however, our results differ from prior studies because consent options did not dominate the deliberations. Jurors saw consent as important but were able to set it aside as an assumed prerequisite for sharing data to focus discussion and recommendation on other conditions. Overall, the citizen jury or community jury method of deliberation was successful and would be a valuable approach for informing health policymaking in Singapore.

Supplemental Material

sj-docx-1-bds-10.1177_20539517221108988 - Supplemental material for Sharing precision medicine data with private industry: Outcomes of a citizens’ jury in Singapore

Supplemental material, sj-docx-1-bds-10.1177_20539517221108988 for Sharing precision medicine data with private industry: Outcomes of a citizens’ jury in Singapore by Angela Ballantyne, Tamra Lysaght, Hui Jin Toh, Serene Ong, Andrew Lau, G Owen Schaefer, Vicki Xafis, E Shyong Tai, Ainsley J Newson, Stacy Carter, Chris Degeling and Annette Braunack-Mayer in Big Data & Society

Footnotes

Acknowledgements

The authors would like to thank the following Advisory Group members for their guidance and insights: Koh Mingshi, Director, Chief Health Scientist Office, Ministry of Health Singapore; Long Chey May, Group Chief Patient Officer, Patient Advocacy and Support Office, National University Health System; Gan Sulin, Deputy Director, Research & Strategic Messaging, Ministry of Health Singapore; Sutowo Wong, Director, Analytics and Information Management Division, Ministry of Health Singapore; Sim Xueling, Assistant Professor, Saw Swee Hock School of Public Health, National University of Singapore; Patrick Tan, Executive Director, Precision Health Research Singapore. We also thank Belinda Fabrianesi, Research Assistant, Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, University of Wollongong.

Declaration of conflicting interests

E Shyong Tai is Director of the Centre for Precision Health at the National University Hospital System, which has received grants from the National Medical Research Council and the National Institutes of Health to conduct studies that involve analysis and sharing of de-identified genetic data. E Shyong Tai is also the co-chair of the Precision Medicine Steering Committee (appointed by the Ministry of Health) with specific responsibility for the Public and Community Trust Workgroup. Owen Schaefer is a member of that Workgroup.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Ministry of Education, Singapore, (grant number MOE2017-SSRTG-028) the National Research Foundation White Space funding administered by the Singapore Ministry of Health's National Medical Research Council as part of the National Precision Medicine strategy.

Ethics approval and consent to participate

We obtained an ethics review exemption to conduct this research from the National University of Singapore – Institutional Review Board (IRB) (NUS-IRB-2020-172). All participants gave their written consent and received an information sheet explaining the aims, benefits and risks of the study.

ORCID iDs

Tamra Lysaght

Hui Jin Toh

Serene Ong

Vicki Xafis

E Shyong Tai

G Owen Schaefer

Ainsley J Newson

Stacy Carter

Chris Degeling

Annette Braunack-Mayer

Supplemental material

Supplemental material for this article is available online.

Notes

References

Ai-Lien

Koh

Khalik

(2021) Data of 14,200 people with HIV leaked online by US fraudster who was deported from Singapore. Available at: https://www.straitstimes.com/singapore/data-of-14200-singapore-patients-with-hiv-leaked-online-by-american-fraudster-who-was (accessed November 11, 2021).

Aitken

de St Jorre

Pagliari

, et al. (2016) Public responses to the sharing and linkage of health data for research purposes: A systematic review and thematic synthesis of qualitative studies. BMC Medical Ethics 1(17): 73.

Akpa-Inyang

Chima

(2021) South African traditional values and beliefs regarding informed consent and limitations of the principle of respect for autonomy in African communities: A cross-cultural qualitative study. BMC Medical Ethics 22(1): 11.

Ballantyne

(2018) Where is the human in the data? A guide to ethical data use. GigaScience 7(7): 1–3.

Birt

Scott

Cavers

, et al. (2016) Member checking: A tool to enhance trustworthiness or merely a nod to validation? Qualitative Health Research 13(26): 1802–1811.

Carter

Graeme

Dixon-Woods

(2015) The social licence for research: Whycare.dataran into trouble. Journal of Medical Ethics 5(41): 404–409.

Chataway

Fry

Marjanovic

, et al. (2012) Public-private collaborations and partnerships in stratified medicine: Making sense of new interactions. New Biotechnology 6(29): 732–740.

Cheah

Piasecki

(2020) Data access committees. BMC Medical Ethics 12: 20.

Chesterman

(2014) Data Protection Law in Singapore: Privacy and Sovereignty in an Interconnected World. Singapore: Academy Publishing.

10.

Chua

(2018) Singapore From social democracy to communitarianism. In: Reese-Schäfer

(ed.) Handbuch Kommunitarismus. Springer VS, Wiesbaden: Springer Reference Geisteswissenschaften, pp. 643-662.

11.

Cindy

(2021) Health Ministry to study if Integrated Shield Plan insurance can be made 'fully portable'. Available at: https://www.channelnewsasia.com/singapore/integrated-shield-plans-insurance-committee-fully-portable-1354091 (accessed November 11, 2021).

12.

Cook-Deegan

Majumder

McGuire

(2019) Introduction: Sharing data in a medical information commons. The Journal of Law, Medicine & Ethics 1(47): 7–11.

13.

Data Futures Partnership (2017) A Path to Social Licence: Guidelines for Trusted Data Use. Available at: https://www.aisp.upenn.edu/wp-content/uploads/2019/08/Trusted-Data-Use_2017.pdf (accessed November 11, 2021).

14.

Degeling

(2019) Deliberative methods. In: Atkinson SD

Hardy

Williams

(eds) Sage Research Methods Foundations. DOI:10.4135/9781526421036827356

15.

Degeling

Carter

van Oijen

, et al. (2020) Community perspectives on the benefits and risks of technologically enhanced communicable disease surveillance systems: A report on four community juries. BMC Medical Ethics 31: 21.

16.

Department of Health and Social Care (2018) The future of healthcare: our vision for digital, data and technology in health and care. Available at: https://www.gov.uk/government/publications/the-future-of-healthcare-our-vision-for-digital-data-and-technology-in-health-and-care/the-future-of-healthcare-our-vision-for-digital-data-and-technology-in-health-and-care#guiding-principles (accessed November 10, 2021).

17.

Dive

Critchley

Otlowski

, et al. (2020) Public trust and global biobank networks. BMC Medical Ethics 73: 21.

18.

Fiore

Goodman

(2016) Precision medicine ethics: Selected issues and developments in next-generation sequencing, clinical oncology, and ethics. Current Opinion in Oncology 1(28): 83–87.

19.

Garrison

Sathe

Antommaria

, 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.

20.

Ghafur

Van Dael

Leis

, et al. (2020) Public perceptions on data sharing: Key insights from the UK and the USA. The Lancet Digital Health 2(9): e444–e446.

21.

Hammack

Brelsford

Beskow

(2019) Thought leader perspectives on participant protections in precision medicine research. The Journal of Law, Medicine & Ethics 1(47): 134–148.

22.

Haskins

(2011) Social Policy in Singapore: A Crucible of Individual Responsibility. Available at: https://www.brookings.edu/articles/social-policy-in-singapore-a-crucible-of-individual-responsibility/ (accessed November 11, 2021).

23.

Hill

Turner

Martin

, 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 (13): 72. DOI: 10.1186/1471-2288-13-72.

24.

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).

25.

Kalkman

van Delden

Banerjee

, 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 3-13.

26.

Karpowitz

Raphael

(2016) Ideals of inclusion in deliberation. Journal of Public Deliberation 12(2): 1–24.

27.

Lee

(2015) Intimacy and family consent: A confucian ideal. The Journal of Medicine and Philosophy 40(4): 418–436.

28.

Lemmens

(2016) "Informed consent". Routledge Handbook of Medical Law and Ethics, 1st ed. Routledge, pp. 27-51.

29.

Lysaght

Ballantyne

Xafis

, et al. (2020) "Who is watching the watchdog?" Ethical perspectives of sharing health-related data for precision medicine in Singapore. BMC Medical Ethics 21: 118.

30.

Lysaght

Ballantyne

Toh

, et al. (2021) Trust and trade-offs in sharing data for precision medicine: A national survey of Singapore. Journal of Personalized Medicine 11(9): 921.

31.

Master

Campo-Engelstein

Caulfield

(2015) Scientists’ perspectives on consent in the context of biobanking research. European Journal of Human Genetics 23: 569–574.

32.

Mcleod

Dolezel

(2018) Cyber-analytics: Modeling factors associated with healthcare data breaches. Decision Support Systems 108: 57–68.

33.

Ministry of Health (2021a) Healthcare Schemes & Subsidies. Available at: https://www.moh.gov.sg/cost-financing/healthcare-schemes-subsidies (accessed November 11, 2021).

34.

Ministry of Health (2021b) Moratorium on Genetic Testing and Insurance. Use of Genetic Test Results in Insurance Underwriting. Available at: https://www.moh.gov.sg/resources-statistics/moratorium-on-genetic-testing-and-insurance (accessed November 11, 2021).

35.

Mohan

Sim

(2019) SingHealth cyberattack: IHiS sacks 2 employees, imposes financial penalty on CEO. Available at: https://www.channelnewsasia.com/news/singapore/singhealth-cyberattack-ihis-fires-employees-ceo-fined-11120838 (accessed November 10, 2021).

36.

National Institute of Health (2020) What is the Precision Medicine Initiative?. Available at: https://ghr.nlm.nih.gov/primer/precisionmedicine/initiative (accessed 10 November, 2021).

37.

O'Neill

(2002) A Question of Trust: BBC Reith Lectures 2002. Cambridge: Cambridge University Press.

38.

Phillips

Dove

Knoppers

(2017) Criminal prohibition of wrongful Re identification: Legal solution or minefield for big data? Bioethical Inquiry (14): 527–539.

39.

PRECISE (2021) Precision Health Research, Singapore Available at: https://www.npm.sg/ (accessed April 15, 2021).

40.

PricewaterhouseCoopers (2019) Key lessons from the Public Report of the Committee of Inquiry (COI) on SingHealth cyber attack. Available at: https://www.pwc.com/sg/en/risk-assurance/assets/coi-on-singhealth-cyber-attack-201901.pdf.

41.

Reason

(1997) Managing the Risks of Organizational Accidents, 1st ed Ashgate.

42.

Reason

(2004) Beyond the organisational accident: The need for "error wisdom" on the frontline. Quality & Safety in Healthcare 13(Suppl 12): ii28–ii33.

43.

Rogers

Ballantyne

(2009) Justice in health research: What is the role of evidence-based medicine? Perspectives in Biology and Medicine 2(52): 188–202.

44.

Sanders

Oberst

(2016) Precision Medicine in China. Washington DC: American Association for the Advancement of Science.

45.

Sankar

Parker

(2017) The precision medicine initiative's all of us research program: An agenda for research on its ethical, legal, and social issues. Genetics in Medicine (19): 743–750. DOI: 10.1038/gim.2016.183.

46.

Schaefer

Tai

Sun

(2019) Precision medicine and big data. Asian Bioethics Review 11: 275–288.

47.

Sheehan

Friesen

Balmer

, et al. (2020) Trust, trustworthiness and sharing patient data for research. Journal of Medical Ethics e26.

48.

Smith

Wales

(2000) Citizens’ juries and deliberative democracy. Political Studies (48): 51–65.

49.

Stockdale

Cassell

Ford

(2019) "Giving something back": A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the republic of Ireland. Wellcome Open Research (3): 6.

50.

Street

Duszynski

Krawczyk

, et al. (2014) The use of citizens’ juries in health policy decision-making: A systematic review. Social Science and Medicine (109): 1–9. DOI: 10.1016/j.socscimed.2014.03.005.

51.

Street

Fabrianesi

Adams

, et al. (2021) Sharing administrative health data with private industry: A report on two citizens’ juries. Health Expectations 4(24): 1337–1348.

52.

Tan

Lam

CSP

Matchar

, et al. (2021) Singapore's health-care system: Key features, challenges, and shifts. The Lancet 398(10305): 1091–1104.

53.

The Lancet (2018) Personalised medicine in the UK. The Lancet 391(10115): e1.

54.

Thomas

(2016) CJCheck stage 1: Development and testing of a checklist for reporting community juries - delphi process and analysis of studies published in 1996-2015. Health Expectations 4: 20.

55.

Tully

Hassan

Oswald

, et al. (2019) Commercial use of health data-A public "trial" by citizens’ jury. Learning Healthcare System 4(3): e10200.

56.

UK Biobank (2007) UK Biobank Ethics and Governance Framework. Available at: https://www.ukbiobank.ac.uk/media/0xsbmfmw/egf.pdf (accessed 11 November, 2021).

57.

U.S Department of State (2020) Singapore 2020 Crime & Safety Report. Available at: https://www.osac.gov/Country/Singapore/Content/Detail/Report/7f0cc2bc-ba9b-4485-b58b-1861aa0f8fc3 (accessed November 11, 2021).

58.

Wang

Zhang

Zhao

(2016) Definition and application of precision medicine. Chinese Journal of Traumatology 5(19): 249–250.

59.

Dou

Chai

, et al. (2019) Large-scale whole-genome sequencing of three diverse Asian populations in Singapore. Cell (179): 736–749.e715.

60.

Xafis

(2015) The acceptability of conducting data linkage research without obtaining consent: Lay people's views and justifications. BMC Medical Ethics 16: 79.

61.

Xiao

Zhou

(2020) Rule of Law and Executive Exemption from the Personal Data Protection Act (PDPA) 2012. Singapore Comparative Law Review 2020 (SCLR 2020) (accessed October 26, 2021).

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.09 MB