BackgroundIn recent years, the amount of genomic data produced in clinical genetics services has increased significantly due to the advent of next-generation sequencing. This influx of genomic information leads to continuous changes in knowledge on how genetic variants relate to hereditary disease. These changes can have important consequences for patients who have had genetic testing in the past, as new information may affect their clinical management. When and how patients should be recontacted after new genetic information becomes available has been investigated extensively. However, the issue of how to handle the changing nature of genetic information remains underexplored in a laboratory setting, despite it being the first stage at which changes in genetic data are identified and managed.MethodsThe authors organized a 7-day online focus group discussion. Fifteen clinical laboratory geneticists took part. All (nine) Dutch clinical molecular genetics diagnostic laboratories were represented.ResultsLaboratories in our study reinterpret genetic variants reactively, e.g. at the request of a clinician or following identification of a previously classified variant in a new patient. Participants currently deemed active, periodic reinterpretation to be unfeasible and opinions differed on whether it is desirable, particularly regarding patient autonomy and the main responsibilities of the laboratory. The efficacy of reinterpretation was questioned in the presence of other strategies, such as reanalysis and resequencing of DNA. Despite absence of formal policy regarding when to issue a new report for clinicians due to reclassified genetic data, participants indicated similar practice across all laboratories. However, practice differed significantly between laboratory geneticists regarding the reporting of VUS reclassifications.ConclusionBased on the results, the authors formulated five challenges needing to be addressed in future laboratory guidelines: 1. Should active reinterpretation of variants be conducted by the laboratory as a routine practice? 2. How does reinterpretation initiated by the laboratory relate to patient expectations and consent? 3. When should reinterpreted data be considered clinically significant and communicated from laboratory to clinician? 4. Should reinterpretation, reanalysis or a new test be conducted? 5. How are reclassifications perceived and how might this affect laboratory practice?

Despite the increasing push towards interdisciplinarity across the physical and social sciences, little is known about the realities of working across such diverse disciplinary boundaries. This article provides empirical insight into the challenges of collaboration from the perspective of a sociologist working on an interdisciplinary project focused on developing a medical device. Findings suggest the effective contribution of sociological research is affected by the framing of interdisciplinary projects. From the beginning, the project pursued a narrow framing focused on scientific development, pushing the sociological research outside the relevance of the project. Reframing is negotiated in shared spaces between disciplines, and fieldwork became important in reframing the project to include the sociological research. However, without commitment to addressing a societal problem, it was impossible for sociology to contribute effectively. Sociologists embarking on similar endeavours should ensure there is shared commitment towards a social issue to prevent the marginalization of sociological research.

Innovation occupies a pivotal place in our understanding of knowledgebased economies, and this is raising questions about sources of innovation, how it originates, and the role played by employees, work practices and learning. This paper explores these issues through case study research into a new approach to providing healthcare for homeless people in England, and by bringing together conceptual insights from the employee-driven innovation literature, and more broadly from social and practice-based learning theory and organisational theory. Applying these perspectives to our case enables illumination of the innovation as a process -not an event -and as an ongoing set of organisational practices that transcend their origins. Through our analysis we argue that the notion of 'a cause' is helpful in elucidating the impetus and the commitment to making the innovation happen (and go on happening). Our findings are presented under three themes: 'establishing a cause' , 'organising for innovation' , and 'innovative capability in practice' . Building on these, we have identified five key interrelated dimensions which help conceptualise the work and learning that it took to create and (re-)enact the innovation and that we suggest may have relevance for understanding and characterising other employee-led innovations in and perhaps beyond healthcare.

Background. In recent years, the amount of genomic data produced in clinical genetics services has increased significantly due to the advent of next-generation sequencing. This influx of genomic information leads to continuous changes in knowledge on how genetic variants relate to hereditary disease. These changes can have important consequences for patients who have had genetic testing in the past, as new information may affect their clinical management. When and how patients should be recontacted after new genetic information becomes available has been investigated extensively.However, the issue of how to handle the changing nature of genetic information is significantly underexplored in a laboratory setting, despite it being the first stage at which changes in genetic data are identified and managed. Methods. The authors organized a 7-day online focus group discussion in which all Dutch molecular genetics diagnostic laboratories were represented. Results. Laboratories in our study reinterpret genetic variants reactively, e.g. at the request of a clinician or following identification of a previously classified variant in a new patient. Participants currently deemed active, periodic reinterpretation to be unfeasible and opinions differed on whether it is desirable, particularly in regard to patient autonomy and the main responsibilities of the laboratory. The efficacy of reinterpretation was questioned in the presence of other strategies, such as reanalysis and resequencing of DNA. Despite absence of formal policy regarding when to issue a new report for clinicians due to reclassified genetic data, participants indicated similar practice across all laboratories. However, practice differed significantly between laboratory geneticists regarding the reporting of VUS reclassifications. Conclusion. Based on the results, the authors formulated five challenges needing to be addressed in future laboratory guidelines: 1. Should active reinterpretation of variants be conducted by the laboratory as a routine practice? 2. How does reinterpretation initiated by the laboratory relate to patient expectations and consent? 3. When should reinterpreted data be considered clinically significant and communicated from laboratory to clinician? 4. Should reinterpretation, reanalysis or a new test be conducted? 5. How are reclassifications perceived and how might this affect laboratory practice?

Centralised, compliance-focused approaches to research ethics have been normalised in practice. In this paper, we argue that the dominance of such systems has been driven by neoliberal approaches to governance, where the focus on controlling and individualising risk has led to an overemphasis of decontextualised ethical principles and the conflation of ethical requirements with the documentation of ‘informed consent’. Using a UK-based case study, involving a point-of-care-genetic test as an illustration, we argue that rather than ensuring ethical practice such compliance-focused approaches may obstruct valuable research. We call for an approach that encourages researchers and research communities—including regulators, ethics committees, funders and publishers of academic research—to acquire skills to make morally appropriate decisions, and not base decision-making solely on compliance with prescriptive regulations. We call this ‘ethical preparedness’ and outline how a research ethics system might make space for this approach.