Coproduction, a collaborative model of research that includes stakeholders in the research process, has been widely advocated as a means of facilitating research use and impact. We summarise the arguments in favour of coproduction, the different approaches to establishing coproductive work and their costs, and offer some advice as to when and how to consider coproduction. Despite the multiplicity of reasons and incentives to coproduce, there is little consensus about what coproduction is, why we do it, what effects we are trying to achieve, or the best coproduction techniques to achieve policy, practice or population health change. Furthermore, coproduction is not free risk or cost. Tensions can arise throughout coproduced research processes between the different interests involved. We identify five types of costs associated with coproduced research affecting the research itself, the research process, professional risks for researchers and stakeholders, personal risks for researchers and stakeholders, and risks to the wider cause of scholarship. Yet, these costs are rarely referred to in the literature, which generally calls for greater inclusion of stakeholders in research processes, focusing exclusively on potential positives. There are few tools to help researchers avoid or alleviate risks to themselves and their stakeholders. First, we recommend identifying specific motivations for coproduction and clarifying exactly which outcomes are required for whom for any particular piece of research. Second, we suggest selecting strategies specifically designed to enable these outcomes to be achieved, and properly evaluated. Finally, in the absence of strong evidence about the impact and process of coproduction, we advise a cautious approach to coproduction. This would involve conscious and reflective research practice, evaluation of how coproduced research practices change outcomes, and exploration of the costs and benefits of coproduction. We propose some preliminary advice to help decide when coproduction is likely to be more or less useful.

Social Impact Bonds (SIBs) are a new mechanism for delivering public services. This article reviews the emerging SIB literature in high‐income settings. It identifies three distinct narratives: a public sector reform narrative; a financial sector reform narrative; and a cautionary narrative. These are analyzed relative to three themes: public versus private values; outcomes contracting; and risk allocation. The first two narratives are complementary and offer a ‘win‐win’ portrayal of SIBs. The third narrative challenges this dominant commentary by highlighting potential risks. There is limited empirical evidence on active SIBs to support these narratives. SIBs may have the potential to align public and private interests while improving outcomes for people affected by entrenched social problems, but this is yet to be established and appears less probable than the third more cautionary narrative. More empirical research is needed to consider the potential risks, drawbacks, benefits and alternatives of SIBs in different settings.

Antimicrobial resistance (AMR) is a global health problem. Bacteria carrying resistance genes can be transmitted between humans, animals and the environment. There are concerns that the widespread use of antimicrobials in the food chain constitutes an important source of AMR in humans, but the extent of this transmission is not well understood. The aim of this review is to examine published evidence on the links between antimicrobial use (AMU) in the food chain and AMR in people and animals. The evidence showed a link between AMU in animals and the occurrence of resistance in these animals. However, evidence of the benefits of a reduction in AMU in animals on the prevalence of resistant bacteria in humans is scarce. The presence of resistant bacteria is documented in the human food supply chain, which presents a potential exposure route and risk to public health. Microbial genome sequencing has enabled the establishment of some links between the presence of resistant bacteria in humans and animals but, for some antimicrobials, no link could be established. Research and monitoring of AMU and AMR in an integrated manner is essential for a better understanding of the biology and the dynamics of antimicrobial resistance.

Background: Researchers are increasingly required to describe the impact of their work, e.g. in grant proposals, project reports, press releases and research assessment exercises. Specialised impact assessment studies can be difficult to replicate and may require resources and skills not available to individual researchers. Researchers are often hard-pressed to identify and describe research impacts and ad hoc accounts do not facilitate comparison across time or projects.Methods: TheResearch Impact Frameworkwas developed by identifying potential areas of health research impact from the research impact assessment literature and based on research assessment criteria, for example, as set out by the UK Research Assessment Exercise panels. A prototype of the framework was used to guide an analysis of the impact of selected research projects at the London School of Hygiene and Tropical Medicine. Additional areas of impact were identified in the process and researchers also provided feedback on which descriptive categories they thought were useful and valid vis-à-vis the nature and impact of their work.Results: We identified four broad areas of impact:I. Research-related impacts;II. Policy impacts;III. Service impacts: health and intersectoral andIV. Societal impacts.Within each of these areas, further descriptive categories were identified. For example, the nature of research impact on policy can be described using the following categorisation, put forward by Weiss:Instrumental usewhere research findings drive policy-making;Mobilisation of supportwhere research provides support for policy proposals;Conceptual usewhere research influences the concepts and language of policy deliberations andRedefining/wider influencewhere research leads to rethinking and changing established practices and beliefs.Conclusion: Researchers, while initially sceptical, found that the Research Impact Framework provided prompts and descriptive categories that helped them systematically identify a range of specific and verifiable impacts related to their work (compared to ad hoc approaches they had previously used). The framework could also help researchers think through implementation strategies and identify unintended or harmful effects. The standardised structure of the framework facilitates comparison of research impacts across projects and time, which is useful from analytical, management and assessment perspectives.

Reorganisation of healthcare services into networks of clinical experts is increasing as a strategy to promote the uptake of evidence based practice and to improve patient care. This is reflected in significant financial investment in clinical networks. However, there is still some question as to whether clinical networks are effective vehicles for quality improvement. The aim of this systematic review was to ascertain the effectiveness of clinical networks and identify how successful networks improve quality of care and patient outcomes. A systematic search was undertaken in accordance with the PRISMA approach in Medline, Embase, CINAHL and PubMed for relevant papers between 1 January 1996 and 30 September 2014. Established protocols were used separately to examine and assess the evidence from quantitative and qualitative primary studies and then integrate findings. A total of 22 eligible studies (9 quantitative; 13 qualitative) were included. Of the quantitative studies, seven focused on improving quality of care and two focused on improving patient outcomes. Quantitative studies were limited by a lack of rigorous experimental design. The evidence indicates that clinical networks can be effective vehicles for quality improvement in service delivery and patient outcomes across a range of clinical disciplines. However, there was variability in the networks’ ability to make meaningful network- or system-wide change in more complex processes such as those requiring intensive professional education or more comprehensive redesign of care pathways. Findings from qualitative studies indicated networks that had a positive impact on quality of care and patients outcomes were those that had adequate resources, credible leadership and efficient management coupled with effective communication strategies and collaborative trusting relationships. There is evidence that clinical networks can improve the delivery of healthcare though there are few high quality quantitative studies of their effectiveness. Our findings can provide policymakers with some insight into how to successfully plan and implement clinical networks by ensuring strong clinical leadership, an inclusive organisational culture, adequate resourcing and localised decision-making authority.