As opposed to a ‘one size fits all’ approach, precision medicine uses relevant biological, medical, behavioural and environmental information about a person to further personalize their healthcare. This could mean better prediction of someone’s disease risk and more effective diagnosis and treatment if they have a condition. Big data allows for far more precision and tailoring than was ever before possible by linking together diverse datasets to reveal hitherto-unknown correlations and causal pathways. But it also raises ethical issues relating to (...) the balancing of interests, viability of anonymization, familial and group implications, as well as genetic discrimination. This article analyses these issues in light of the values of public benefit, justice, harm minimization, transparency, engagement and reflexivity and applies the deliberative balancing approach found in theEthical Framework for Big Data in Health and Research to a case study on clinical genomic data sharing. Please refer to that article for an explanation of how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. Our discussion is meant to be of use to those involved in the practice as well as governance and oversight of precision medicine to address ethical concerns that arise in a coherent and systematic manner. (shrink)

The United States’ ambitious Precision Medicine Initiative proposes to accelerate exponentially the adoption of precision medicine, an approach to health care that tailors disease diagnosis, treatment, and prevention to individual variability in genes, environment, and lifestyle. It aims to achieve this by creating a cohort of volunteers for precision medicine research, accelerating biomedical research innovation, and adopting policies geared toward patients’ empowerment. As strategies to implement the PMI are formulated, critical consideration of the initiative's ethical and sociopolitical dimensions is needed. (...) Drawing on scholarship of nationalism and democracy, we discuss the PMI's construction of what we term “genomic citizenship”; the possible normative obligations arising therefrom; and the ethical, legal, and social challenges that will ensue. Although the PMI is a work in progress, discussion of the existing and emerging issues can facilitate the development of policies, structures, and procedures that can maximize the initiative's ability to produce equitable and socially sensitive outcomes. Our analysis can also be applied to other population-based, precision medicine research programs. (shrink)

Background We aimed to examine the ethical concerns Singaporeans have about sharing health-data for precision medicine and identify suggestions for governance strategies. Just as Asian genomes are under-represented in PM, the views of Asian populations about the risks and benefits of data sharing are under-represented in prior attitudinal research. Methods We conducted seven focus groups with 62 participants in Singapore from May to July 2019. They were conducted in three languages and analysed with qualitative content and thematic analysis. Results Four (...) key themes emerged: nuanced understandings of data security and data sensitivity; trade-offs between data protection and research benefits; trust in the public and private sectors; and governance and control options. Participants were aware of the inherent risks associated with data sharing for research. Participants expressed conditional support for data sharing, including genomic sequence data and information contained within electronic medical records. This support included sharing data with researchers from universities and healthcare institutions, both in Singapore and overseas. Support was conditional on the perceived social value of the research and appropriate de-identification and data security processes. Participants suggested that a data sharing oversight body would help strengthen public trust and comfort in data research for PM in Singapore. Conclusion Maintenance of public trust in data security systems and governance regimes can enhance participation in PM and data sharing for research. Contrary to themes in much prior research, participants demonstrated a sophisticated understanding of the inherent risks of data sharing, analysed trade-offs between risks and potential benefits of PM, and often adopted an international perspective. (shrink)

With the growth of precision medicine research on health data and biospecimens, research institutions will need to build and maintain long-term, trusting relationships with patient-participants. While trust is important for all research relationships, the longitudinal nature of precision medicine research raises particular challenges for facilitating trust when the specifics of future studies are unknown. Based on focus groups with racially and ethnically diverse patients, we describe several factors that influence patient trust and potential institutional approaches to building trustworthiness. Drawing on (...) these findings, we suggest several considerations for research institutions seeking to cultivate long-term, trusting relationships with patients: Address the role of history and experience on trust, engage concerns about potential group harm, address cultural values and communication barriers, and integrate patient values and expectations into oversight and governance structures. (shrink)

Robust technology infrastructure is needed to enable learning health care systems to improve quality, access, and cost. Such infrastructure relies on the trust and confidence of individuals to share their health data for healthcare and research. Few studies have addressed consumers’ views on electronic data sharing and fewer still have explored the dual purposes of healthcare and research together. The objective of the study is to explore factors that affect consumers’ willingness to share electronic health information for healthcare and research. (...) This study involved a random-digit dial telephone survey of 800 adult Californians conducted in English and Spanish. Logistic regression was performed using backward selection to test for significant associations of each explanatory variable with the outcome variable. The odds of consent for electronic data sharing for healthcare decreased as Likert scale ratings for EHR impact on privacy worsened, odds ratio = 0.74, 95% CI [0.60, 0.90]; security, OR = 0.80, 95% CI [0.66, 0.98]; and quality, OR = 0.59, 95% CI [0.46–0.75]. The odds of consent for sharing for research was greater for those who think EHR will improve research quality, OR = 11.26, 95% CI [4.13, 30.73]; those who value research benefit over privacy OR = 2.72, 95% CI [1.55, 4.78]; and those who value control over research benefit OR = 0.49, 95% CI [0.26, 0.94]. Consumers’ choices about electronically sharing health information are affected by their attitudes toward EHRs as well as beliefs about research benefit and individual control. Design of person-centered interventions utilizing electronically collected health information, and policies regarding data sharing should address these values of importance to people. Understanding of these perspectives is critical for leveraging health data to support learning health care systems. (shrink)

IntroductionInternational sharing of health data opens the door to the study of the so-called ‘Big Data’, which holds great promise for improving patient-centred care. Failure of recent data sharing initiatives indicates an urgent need to invest in societal trust in researchers and institutions. Key to an informed understanding of such a ‘social license’ is identifying the views patients and the public may hold with regard to data sharing for health research.MethodsWe performed a narrative review of the empirical evidence addressing patients’ (...) and public views and attitudes towards the use of health data for research purposes. The literature databases PubMed, Embase, Scopus and Google Scholar were searched in April 2019 to identify relevant publications. Patients’ and public attitudes were extracted from selected references and thematically categorised.ResultsTwenty-seven papers were included for review, including both qualitative and quantitative studies and systematic reviews. Results suggest widespread—though conditional—support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of data research, they expressed concerns about breaches of confidentiality and potential abuses of the data. Studies showed agreement on the following conditions: value, privacy, risk minimisation, data security, transparency, control, information, trust, responsibility and accountability.ConclusionsOur results indicate that a social license for data-intensive health research cannot simply be presumed. To strengthen the social license, identified conditions ought to be operationalised in a governance framework that incorporates the diverse patient and public values, needs and interests. (shrink)

Since the late 1980s, the human genetics and genomics research community has been promising to usher in a “new paradigm for health care”—one that uses molecular profiling to identify human genetic variants implicated in multifactorial health risks. After the completion of the Human Genome Project in 2003, a wide range of stakeholders became committed to this “paradigm shift,” creating a confluence of investment, advocacy, and enthusiasm that bears all the marks of a “scientific/intellectual social movement” within biomedicine. Proponents of this (...) movement usually offer four ways in which their approach to medical diagnosis and health care improves upon current practices, arguing that it is more “personalized,” “predictive,” “preventive,” and “participatory” than the medical status quo. Initially, it was personalization that seemed to best sum up the movement's appeal. By 2012, however, powerful opinion leaders were abandoning “personalized medicine” in favor of a new label: “precision medicine.” The new label received a decisive seal of approval when, in January 2015, President Obama unveiled plans for a national “precision medicine initiative” to promote the development and use of genomic tools in health care. (shrink)

This article reviews the history of medical and research abuses experienced by American Indians since European colonization. This article examines the unethical research of American Indians/Alaska Natives in light of the Tuskegee Study of Untreated Syphilis in the Negro Male. Literature citations indicate that significant unethical research and medical care incidents occurred both before and after the Tuskegee Syphilis Study among American Indians/Alaska Natives. The majority of these unethical abuses were committed by the federal government and within the historical context (...) of a long-term contentious relationship between American Indians and the federal government. Although President Clinton issued a highly visible public apology to the African American survivors of the Tuskegee syphilis experiment in 1997, American Indians have yet to experience such visible federal acknowledgment. To ensure ethical research in which benefits outweigh risks and findings are not value-laden or misrepresented, tribes have instituted their own Institutional Review Boards coupled with community-participatory activities. (shrink)

In recent years, discourses around “personalized,” “stratified,” and “precision” medicine have proliferated. These concepts broadly refer to the translational potential carried by new data-intensive biomedical research modes. Each describes expectations about the future of medicine and healthcare that data-intensive innovation promises to bring forth. The definitions and uses of the concepts are, however, plural, contested and characterized by diverse ideas about the kinds of futures that are desired and desirable. In this paper, we unpack key disputes around the “personalized,” “stratified,” (...) and “precision” terms, and map the epistemic, political and economic contexts that structure them as well as the different roles attributed to patients and citizens in competing future imaginaries. We show the ethical and value baggage embedded within the promises that are manufactured through terminological choices and argue that the context and future-oriented nature of these choices helps to understanding how data-intensive biomedical innovations are made socially meaningful. (shrink)

Personalized medicine aims to tailor disease prevention, diagnosis, and treatment to individuals on the basis of their genes, lifestyle and environments. Patient and interest organizations may potentially play an important role in the realization of PM. This paper investigates the views and perspectives on PM of a variety of PIOs. Semi-structured telephone interviews were conducted among leading representatives of 13 PIOs located in Europe and North-America. The data collected were analysed using a conventional content analysis approach. The PIO representatives supported (...) the realization of PM but feared that many financial, structural and organizational challenges may delay its realization. They encouraged strategies to modernize drug licencing mechanisms, develop research and data sharing infrastructures, and educate patients and health care professionals in PM. Notably, they emphasized the importance of developing PM in an equitable way and taking into consideration the patients’ needs, values and personal situation. Despite varying levels of awareness regarding PM, the PIO representatives expressed willingness to engage in the PM agenda and recommended that PIOs work closely with policy-makers to design PM in a way that truly addresses the needs and concerns of patients. PIOs have the potential to become central drivers of the PM agenda. Collaborations should be further developed between PIOs, researchers, drug developers and health care authorities. (shrink)

Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and (...) Policy-relevant Ethics in Singapore Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AI-assisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data. (shrink)