Suchergebnisse

Background: In Australia, national policy prioritises the integration of clinical genetic data with networked electronic medical records (EMRs) for enhanced coordination of care and clinical decision-making. Objective: To examine the needs, privacy expectations and concerns of patients, family members, patient advocates and clinicians in relation to the use of networked EMRs for clinical genetic information. Method: Purposive sampling was used to recruit 27 participants for a semi-structured qualitative interview, primarily over Zoom. The interviews were audio and video-recorded and externally transcribed. Interview transcripts were then coded and analysed in NVivo, using an inductive thematic approach. Results: Thematic analysis revealed diverse preferences regarding genetic information access and handling across participants, with five core themes being identified: degree of access and control; central role of genetic professionals as information gatekeepers; complexities of familial implications; external risks; and law, governance and policy; all strong themes that emerged across numerous participants. Conclusion: This project yielded unprecedented and significant insights into the views, needs and concerns of key stakeholders in Australia regarding the inclusion of health-related genetic test results in networked EMRs. Implications: These findings provide a critical reference point for much-needed law reform and policy-making around genetic test results in Australia.

The volume, variety and velocity of data available to companies about their employees is already significant and likely to increase. Employers hold data about employees that could be used to explore the relationship between workplace practice in their organisation and risks to employee health. However, there is significant uncertainty about whether employers subject to English law are permitted to use this data for this purpose, and even whether they may be under a legal obligation to do so. In this article, the question of whether employers are legally permitted or legally obliged to use employee data to identify associations between workplace practice and risk to employee health is answered through an analysis of two spheres of English Law: data protection law, and health and safety law. The authors establish a hypothetical case study concerning a company that wishes to use employee data in this way, to illuminate a set of detailed legal issues. In particular, the question of whether a reasonable and prudent employer is under an obligation under health and safety law to use the data and analytic tools at his or her disposal to assess risk and inform his or her actions is considered. Also addressed is the question of whether such processing would satisfy the data protection law principles of "lawful, fair, and transparent" processing and that of "purpose limitation". A complex picture emerges. The analysis reveals that data protection legislation may not support a trend towards the re-use of employee data to enhance workplace health and safety; nor is there currently a clear mandate that responsible employers use data in this way. The line between useful insight into workplace practices and intrusion into employees' privacy remains blurred.

'Digital Mega-Studies' are entirely or extensively digitised, longitudinal, population-scale initiatives, collecting, storing, and making available individual-level research data of different types and from multiple sources, shaped by technological developments and unforeseeable risks over time. The Australian 'Gen V' project exemplifies this new research paradigm. In 2019, we undertook a multidisciplinary, multi-stakeholder process to map Digital Mega-Studies' key characteristics, legal and governance challenges and likely solutions. We conducted large and small group processes within a one-day symposium and directed online synthesis and group prioritisation over subsequent weeks. We present our methods (including elicitation, affinity mapping and prioritisation processes) and findings, proposing six priority governance principles across three areas—data, participation, trust—to support future high-quality, large-scale digital research in health.

The Aotearoa New Zealand Integrated Data Infrastructure (IDI) is a national database containing a wide range of data about people and households. There is limited information about public views regarding its use for research. A qualitative study was undertaken to examine the views of forty individuals attending a large hospital in Auckland, including those of Māori ethnicity and young people. Semi-structured interview data were analysed using Braun and Clarke's method of thematic analysis. Seven key themes emerged: 1) Limited knowledge about medical data held in national databases; 2) Conditional support for the use of the IDI, including for research; 3) Concerns regarding the misuse of IDI data; 4) The importance of privacy; 5) Different views regarding consent for use of data for research; 6) Desire for access to personal data and the results of research; and 7) Concerns regarding third party and commercial use. Young people and those of Māori ethnicity were more wary of data misuse than others. Although there is reasonable support for the secondary use of public administrative data in the IDI for research, there is more work to be done to ensure ethical and culturally appropriate use of this data via improved consent privacy management processes and researcher training.

Dynamic consent (DC) is an approach to consent that enables people, through an interactive digital interface, to make granular decisions about their ongoing participation. This approach has been explored within biomedical research, in fields such as biobanking and genomics, where ongoing contact is required with participants. It is posited that DC can enhance decisional autonomy and improve researcher–participant communication. Currently, there is a lack of evidence about the measurable effects of DC-based tools. This article outlines a framework for DC evaluation and reporting. The article draws upon the evidence for enhanced modes of informed consent for research as the basis for a logic model. It outlines how future evaluations of DC should be designed to maximize their quality, replicability, and relevance based on this framework. Finally, the article considers best-practice for reporting studies that assess DC, to enable future research and implementation to build upon the emerging evidence base.