Evidence-informed capacity building for setting health priorities in low- and middle-income countries: : A framework and recommendations for further research

Priority-setting in health is risky and challenging, particularly in resource-constrained settings. It is not simply a narrow technical exercise, and involves the mobilisation of a wide range of capacities among stakeholders – not only the technical capacity to “do” research in economic evaluations. Using the Individuals, Nodes, Networks and Environment (INNE) framework, we identify those stakeholders, whose capacity needs will vary along the evidence-to-policy continuum. Policymakers and healthcare managers require the capacity to commission and use relevant evidence (including evidence of clinical and cost-effectiveness, and of social values); academics need to understand and respond to decision-makers’ needs to produce relevant research. The health system at all levels will need institutional capacity building to incentivise routine generation and use of evidence. Knowledge brokers, including priority-setting agencies (such as England’s National Institute for Health and Care Excellence, and Health Interventions and Technology Assessment Program, Thailand) and the media can play an important role in facilitating engagement and knowledge transfer between the various actors. Especially at the outset but at every step, it is critical that patients and the public understand that trade-offs are inherent in priority-setting, and careful efforts should be made to engage them, and to hear their views throughout the process. There is thus no single approach to capacity building; rather a spectrum of activities that recognises the roles and skills of all stakeholders. A range of methods, including formal and informal training, networking and engagement, and support through collaboration on projects, should be flexibly employed (and tailored to specific needs of each country) to support institutionalisation of evidence-informed priority-setting. Finally, capacity building should be a two-way process; those who build capacity should also attend to their own capacity development in order to sustain and improve impact

Patterns of HIV testing practices among young gay and bisexual men living in Scotland: a qualitative study

Abstract Background Increasing overall rates, and frequency, of HIV testing in populations at risk is a key public health objective and a critical dimension of HIV prevention efforts. In the UK, men who have sex with men (MSM) remain one of the communities most at risk of HIV and, within this, young gay men are a key risk group. Understanding HIV testing practices is important in the development of interventions to promote testing among young gay and bisexual men. Methods Qualitative interviews were conducted with thirty young gay and bisexual men (aged 18–29) in Scotland. Thematic analysis of men’s accounts of their approach to HIV testing identified three overarching patterns of testing: ‘habitual’, ‘reactive’ and ‘ ad hoc’. Results This qualitative study, the first to explore patterns of HIV testing practices among young gay and bisexual men in the UK, contributes novel findings around the role of social support and ‘community’ in shaping young men’s approaches to HIV testing. The findings suggest that social support can play an important role in encouraging and facilitating HIV testing among young gay men, however, social norms of non-testing also have the potential to act as a barrier to development of a regular routine. Men with habitual testing practices framed HIV testing as both a personal and ‘community’ responsibility, and more effective than testing in response to risk events or emergent symptoms. Men who reported reactive testing practices described testing for HIV primarily in response to perceived exposure to sexual risk, along with ‘transitional moments’ such as starting, ending or changes to a relationship. Among young men who reported testing on an ad hoc basis, inconvenience and disruptions to HIV testing practices, particularly where men lacked social support, acted as a barrier to developing a routine of regular testing. Conclusions Our findings suggest that interventions which seek to increase rates of HIV testing and testing frequency among young gay and bisexual men should include a specific focus on promoting and supporting positive testing practices within young men’s friendship groups and wider gay communities

Factors impacting HIV testing: A review - Perspectives from Australia, Canada, and the UK

With the current global focus on strengthening HIV prevention through greater testing and treatment uptake, it is increasingly salient to identify and address barriers to testing. A review of the published, peer-reviewed literature and national reports from Australia, Canada, and the UK (2003-2013) on barriers to HIV testing was conducted to provide new information relevant to Australia and to complement earlier reviews from Canada and the UK. A systematic database search using keywords and a set of inclusion criteria yielded 36 studies (Australia = 13; Canada = 6; and the UK = 17). In addition 17 unpublished reports were included in the review. Our study uses a novel, comprehensive framework to describe barriers to HIV testing, and thus contributes to moving beyond the traditional patient-provider-system categorization. Within that framework, barriers are categorized as either intrapersonal (reported in 15 studies), interpersonal (21), or extrapersonal (16) and conceptualized within wider sociocultural and structural contexts. People's abilities and motivations to test (intrapersonal factors) are influenced by a host of interconnected factors spanning relationship (interpersonal) and broader socioeconomic, political and cultural (extrapersonal) factors. We suggest that the relative effects of interventions targeting barriers to HIV testing at the intrapersonal and interpersonal levels are limited by the extent to which the social determinants of health are addressed. The framework may also lend itself to thinking about the enabling factors for HIV testing, and future research may investigate the application of that framework for strategizing the most effective response. Future studies should also capture the lived experiences of barriers to HIV testing experienced by patients, especially in populations which are hard to reach based on social and geographic distance. Context-specific studies to evaluate the feasibility and effectiveness of various interventions proposed in the literature to address barriers to HIV testing are needed

Optimisation: Defining and exploring a concept to enhance the impact of public health initiatives

© 2019 The Author(s). Background: Repeated, data-driven optimisation processes have been applied in many fields to rapidly transform the performance of products, processes and interventions. While such processes may similarly be employed to enhance the impact of public health initiatives, optimisation has not been defined in the context of public health and there has been little exploration of its key concepts. Methods: We used a modified, three-round Delphi study with an international group of researchers, public health policy-makers and practitioners to (1) generate a consensus-based definition of optimisation in the context of public health and (2i) describe key considerations for optimisation in that context. A pre-workshop literature review and elicitation of participant views regarding optimisation in public health (round 1) were followed by a daylong workshop and facilitated face-to-face group discussions to refine the definition and generate key considerations (round 2); finally, post-workshop discussions were undertaken to refine and finalise the findings (round 3). A thematic analysis was performed at each round. Study findings reflect an iterative consultation process with study participants. Results: Thirty of 33 invited individuals (91%) participated in the study. Participants reached consensus on the following definition of optimisation in public health: "A deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints". A range of optimisation considerations were explored. Optimisation was considered most suitable when existing public health initiatives are not sufficiently effective, meaningful improvements from an optimisation process are anticipated, quality data to assess impacts are routinely available, and there are stable and ongoing resources to support it. Participants believed optimisation could be applied to improve the impacts of an intervention, an implementation strategy or both, on outcomes valued by stakeholders or end users. While optimisation processes were thought to be facilitated by an understanding of the mechanisms of an intervention or implementation strategy, no agreement was reached regarding the best approach to inform decisions about modifications to improve impact. Conclusions: The study findings provide a strong basis for future research to explore the potential impact of optimisation in the field of public health

Optimisation: defining and exploring a concept to enhance the impact of public health initiatives

Background: Repeated, data-driven optimisation processes have been applied in many fields to rapidly transform the performance of products, processes and interventions. While such processes may similarly be employed to enhance the impact of public health initiatives, optimisation has not been defined in the context of public health and there has been little exploration of its key concepts. Methods: We used a modified, three-round Delphi study with an international group of researchers, public health policy-makers and practitioners to (1) generate a consensus-based definition of optimisation in the context of public health and (2i) describe key considerations for optimisation in that context. A pre-workshop literature review and elicitation of participant views regarding optimisation in public health (round 1) were followed by a daylong workshop and facilitated face-to-face group discussions to refine the definition and generate key considerations (round 2); finally, post-workshop discussions were undertaken to refine and finalise the findings (round 3). A thematic analysis was performed at each round. Study findings reflect an iterative consultation process with study participants. Results: Thirty of 33 invited individuals (91%) participated in the study. Participants reached consensus on the following definition of optimisation in public health: “A deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints”. A range of optimisation considerations were explored. Optimisation was considered most suitable when existing public health initiatives are not sufficiently effective, meaningful improvements from an optimisation process are anticipated, quality data to assess impacts are routinely available, and there are stable and ongoing resources to support it. Participants believed optimisation could be applied to improve the impacts of an intervention, an implementation strategy or both, on outcomes valued by stakeholders or end users. While optimisation processes were thought to be facilitated by an understanding of the mechanisms of an intervention or implementation strategy, no agreement was reached regarding the best approach to inform decisions about modifications to improve impact. Conclusions: The study findings provide a strong basis for future research to explore the potential impact of optimisation in the field of public health.Other UBCNon UBCReviewedFacult