Public Attitudes Toward Precision Medicine: A Nationwide Survey on Developing a National Cohort Program for Citizen Participation in the Republic of Korea

Public perceptions and attitudes of the national project of bio-big data: A nationwide survey in the Republic of Korea

Background: The National Project of Bio-Big Data (NPBBD) is a South Korean bio-big data collection project, expected to include health, genomic, and lifelog data of one million Koreans. The Ethical, Legal, and Social Implications study is a parallel study active since 2020. As part of the study, a public survey was conducted to evaluate public attitudes towards engagement schemes, such as public committees and web portals for communication between the public and researchers. Methods: An online survey was conducted from March 3-9, 2021, using structured questionnaires addressed to 1,000 adults aged 20-59 years. Results: Several respondents reported a positive attitude towards participation (43.6% "somewhat," 14.3% "definitely"), whereas approximately one-third (36.5%) reported a neutral attitude. Positive factors that may affect the willingness of the respondents to participate included receiving health information (25.1%), contributing to research on cancer and rare diseases (21.9%), and advancing personalized medicine (21.5%). Conversely, negative factors were mainly associated with concerns regarding the risk of data leakage (22.8%), discrimination (21.1%), lack of information (13.5%), possibility of knowing the risk of being diagnosed with an incurable diseases (12.5%), and possibility of using data in industry (11.3%). In terms of project governance, respondents tended to recognize the importance of public participation in incorporating public opinion into the project design. Conclusion: These results have implications for the participant recruitment process, public engagement strategies, and the scope of user (academics/industry, domestic/overseas) accessibility to the database.

Developing Data Sharing Models for Health Research with Real-World Data: A Scoping Review of Patient and Public Preferences

For researchers to realize the benefits of real-world data in healthcare requires broader access to patient data than is currently possible given siloed data systems. To facilitate evidence generation, infrastructure must support integrated data collection and sharing enabled by patient consent. Critical to the success of data sharing is to design secured data sharing platforms around patient preferences and expectations. The objective of this review was to characterize patient and public preferences for secured data sharing platforms and incentives to share real-world data for health research. We conducted a scoping review of the data sharing and health informatics literature capturing patient and public values for data sharing platforms and incentivization. We searched Embase and Medline (OVID) databases for primary data studies. Two reviewers participated in study selection and data abstraction. Findings were summarized according to preference frequency within each major theme. The final search produced 253 articles. After screening, 12 articles were included for data extraction. Two studies discussed preferences for data sharing platforms, 7 discussed incentives preferences, and 3 addressed both. We identified considerable variation of patient and public preferences according to preferred consent mechanisms and level of control, willingness to trade off risks and benefits, and the type of incentivization appropriate to offer for participation. This preference variation informs the conditions under which individuals may be willing to engage with secured data sharing platforms to support research. Our findings indicate that platforms will need to be flexible to meet the diverse preferences of users and facilitate uptake.

Towards a Democratization of Data in the Context of Industry 4.0

Data-driven transparency in end-to-end operations in real-time is seen as a key benefit of the fourth industrial revolution. In the context of a factory, it enables fast and precise diagnoses and corrections of deviations and, thus, contributes to the idea of an agile enterprise. Since a factory is a complex socio-technical system, multiple technical, organizational and cultural capabilities need to be established and aligned. In recent studies, the underlying broad accessibility of data and corresponding analytics tools are called “data democratization”. In this study, we examine the status quo of the relevant capabilities for data democratization in the manufacturing industry. (1) and outline the way forward. (2) The insights are based on 259 studies on the digital maturity of factories from multiple industries and regions of the world using the acatech Industrie 4.0 Maturity Index as a framework. For this work, a subset of the data was selected. (3) As a result, the examined factories show a lack of capabilities across all dimensions of the framework (IT systems, resources, organizational structure, culture). (4) Thus, we conclude that the outlined implementation approach needs to comprise the technical backbone for a data pipeline as well as capability building and an organizational transformation.

A Genomic Information Management System for Maintaining Healthy Genomic States and Application of Genomic Big Data in Clinical Research

Improvements in next-generation sequencing (NGS) technology and computer systems have enabled personalized therapies based on genomic information. Recently, health management strategies using genomics and big data have been developed for application in medicine and public health science. In this review, I first discuss the development of a genomic information management system (GIMS) to maintain a highly detailed health record and detect diseases by collecting the genomic information of one individual over time. Maintaining a health record and detecting abnormal genomic states are important; thus, the development of a GIMS is necessary. Based on the current research status, open public data, and databases, I discuss the possibility of a GIMS for clinical use. I also discuss how the analysis of genomic information as big data can be applied for clinical and research purposes. Tremendous volumes of genomic information are being generated, and the development of methods for the collection, cleansing, storing, indexing, and serving must progress under legal regulation. Genetic information is a type of personal information and is covered under privacy protection; here, I examine the regulations on the use of genetic information in different countries. This review provides useful insights for scientists and clinicians who wish to use genomic information for healthy aging and personalized medicine.

Trust and Trade-Offs in Sharing Data for Precision Medicine: A National Survey of Singapore

BACKGROUND

Precision medicine (PM) programs typically use broad consent. This approach requires maintenance of the social license and public trust. The ultimate success of PM programs will thus likely be contingent upon understanding public expectations about data sharing and establishing appropriate governance structures. There is a lack of data on public attitudes towards PM in Asia.

METHODS

The aim of the research was to measure the priorities and preferences of Singaporeans for sharing health-related data for PM. We used adaptive choice-based conjoint analysis (ACBC) with four attributes: uses, users, data sensitivity and consent. We recruited a representative sample of n = 1000 respondents for an in-person household survey.

RESULTS

Of the 1000 respondents, 52% were female and majority were in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). A total of 64% were generally willing to share de-identified health data for IRB-approved research without re-consent for each study. Government agencies and public institutions were the most trusted users of data. The importance of the four attributes on respondents' willingness to share data were: users (39.5%), uses (28.5%), data sensitivity (19.5%), consent (12.6%). Most respondents found it acceptable for government agencies and hospitals to use de-identified data for health research with broad consent. Our sample was consistent with official government data on the target population with 52% being female and majority in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%).

CONCLUSIONS

While a significant body of prior research focuses on preferences for consent, our conjoint analysis found consent was the least important attribute for sharing data. Our findings suggest the social license for PM data sharing in Singapore currently supports linking health and genomic data, sharing with public institutions for health research and quality improvement; but does not support sharing with private health insurers or for private commercial use.

Public willingness to participate in personalized health research and biobanking: A large-scale Swiss survey

This paper reports survey findings on the Swiss public's willingness, attitudes, and concerns regarding personalized health research participation by providing health information and biological material. The survey reached a sample of 15,106 Swiss residents, from which we received 5,156 responses (34.1% response rate). The majority of respondents were aware of research using human biological samples (71.0%) and held a positive opinion towards this type of research (62.4%). Of all respondents, 53.6% indicated that they would be willing to participate in a personalized health research project. Willingness to participate was higher in younger, higher educated, non-religious respondents with a background in the health sector. Respondents were more willing to provide 'traditional' types of health data, such as health questionnaires, blood or biological samples, as opposed to social media or app-related data. All respondents valued the return of individual research results, including risk for diseases for which no treatment is available. Our findings highlight that alongside general positive attitudes towards personalized health research using data and samples, respondents have concerns about data privacy and re-use. Concerns included potential discrimination, confidentiality breaches, and misuse of data for commercial or marketing purposes. The findings of this large-scale survey can inform Swiss research institutions and assist policymakers with adjusting practices and developing policies to better meet the needs and preferences of the public. Efforts in this direction could focus on research initiatives engaging in transparent communication, education, and engagement activities, to increase public understanding and insight into data sharing activities, and ultimately strengthen personalized health research efforts.

Welfare Genome Project: A Participatory Korean Personal Genome Project With Free Health Check-Up and Genetic Report Followed by Counseling

The Welfare Genome Project (WGP) provided 1,000 healthy Korean volunteers with detailed genetic and health reports to test the social perception of integrating personal genetic and healthcare data at a large-scale. WGP was launched in 2016 in the Ulsan Metropolitan City as the first large-scale genome project with public participation in Korea. The project produced a set of genetic materials, genotype information, clinical data, and lifestyle survey answers from participants aged 20–96. As compensation, the participants received a free general health check-up on 110 clinical traits, accompanied by a genetic report of their genotypes followed by genetic counseling. In a follow-up survey, 91.0% of the participants indicated that their genetic reports motivated them to improve their health. Overall, WGP expanded not only the general awareness of genomics, DNA sequencing technologies, bioinformatics, and bioethics regulations among all the parties involved, but also the general public’s understanding of how genome projects can indirectly benefit their health and lifestyle management. WGP established a data construction framework for not only scientific research but also the welfare of participants. In the future, the WGP framework can help lay the groundwork for a new personalized healthcare system that is seamlessly integrated with existing public medical infrastructure.