Project description:BackgroundIn 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025.MethodsWe used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts.ResultsNine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour.ConclusionThese findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed.

Project description:BackgroundAs highly effective hepatitis C virus (HCV) therapies emerge, data are needed to inform the development of interventions to improve HCV treatment rates. We used simulation modeling to estimate the impact of loss to follow-up on HCV treatment outcomes and to identify intervention strategies likely to provide good value for the resources invested in them.MethodsWe used a Monte Carlo state-transition model to simulate a hypothetical cohort of chronically HCV-infected individuals recently screened positive for serum HCV antibody. We simulated four hypothetical intervention strategies (linkage to care; treatment initiation; integrated case management; peer navigator) to improve HCV treatment rates, varying efficacies and costs, and identified strategies that would most likely result in the best value for the resources required for implementation.Main measuresSustained virologic responses (SVRs), life expectancy, quality-adjusted life expectancy (QALE), costs from health system and program implementation perspectives, and incremental cost-effectiveness ratios (ICERs).ResultsWe estimate that imperfect follow-up reduces the real-world effectiveness of HCV therapies by approximately 75%. In the base case, a modestly effective hypothetical peer navigator program maximized the number of SVRs and QALE, with an ICER compared to the next best intervention of $48,700/quality-adjusted life year. Hypothetical interventions that simultaneously addressed multiple points along the cascade provided better outcomes and more value for money than less costly interventions targeting single steps. The 5-year program cost of the hypothetical peer navigator intervention was $14.5 million per 10,000 newly diagnosed individuals.ConclusionsWe estimate that imperfect follow-up during the HCV cascade of care greatly reduces the real-world effectiveness of HCV therapy. Our mathematical model shows that modestly effective interventions to improve follow-up would likely be cost-effective. Priority should be given to developing and evaluating interventions addressing multiple points along the cascade rather than options focusing solely on single points.

Project description:BackgroundCommunicating research to policymakers is a complex and difficult process. Ensuring that communication materials have information or design aspects that appeal to groups of policymakers with different priorities could be a substantive improvement over current dissemination approaches. To facilitate a more nuanced design of policy communication materials and message framing, we identified and characterized groups of state legislators based on how they prioritize different characteristics of research.MethodsWe used deidentified data collected in 2012 on 862 state legislators belonging to the US liberal-moderate-conservative ideological spectrum and from all 50 US states. Legislators were grouped using latent class analysis based on how they prioritized 12 different characteristics of research (e.g., research is unbiased, presents data on cost-effectiveness, policy options are feasible). We fit initial models using 1-6 group solutions and chose the final model based on identification, information criteria, and substantive interpretation.ResultsMost legislators placed a high priority on research that was understandable (61%), unbiased (61%), available at the time that decisions are made (58%), and brief and concise (55%). The best model identified four groups of state legislators. Pragmatic consumers (36%) prioritized research that was brief and concise, provided cost-effectiveness analyses, and was understandably written. Uninterested skeptics (30%) generally did not place a high priority on any of the research characteristics. Conversely, one-quarter of legislators (25%) belonged to the Highly Informed Supporters group that placed a high priority on most characteristics of research. Finally, Constituent-Oriented Decision Makers (9%) prioritized research that was relevant to their constituents, delivered by someone they knew or trusted, available at the time decisions were made, and dealt with an issue that they felt was a priority for state legislative action.ConclusionsTo maximize the impact of dissemination efforts, researchers should consider how to communicate with legislators who have distinct preferences, values, and priorities. The groups identified in this study could be used to develop communication materials that appeal to a wide range of legislators with distinct needs and preferences, potentially improving the uptake of research into the policymaking process. Future work should investigate how to engage skeptical legislators.

Project description:Operational research (OR) is the discipline of using models, either quantitative or qualitative, to aid decision-making in complex implementation problems. The methods of OR have been used in healthcare since the 1950s in diverse areas such as emergency medicine and the interface between acute and community care; hospital performance; scheduling and management of patient home visits; scheduling of patient appointments; and many other complex implementation problems of an operational or logistical nature.To date, there has been limited debate about the role that operational research should take within implementation science. I detail three such roles for OR all grounded in upfront system thinking: structuring implementation problems, prospective evaluation of improvement interventions, and strategic reconfiguration. Case studies from mental health, emergency medicine, and stroke care are used to illustrate each role. I then describe the challenges for applied OR within implementation science at the organisational, interventional, and disciplinary levels. Two key challenges include the difficulty faced in achieving a position of mutual understanding between implementation scientists and research users and a stark lack of evaluation of OR interventions. To address these challenges, I propose a research agenda to evaluate applied OR through the lens of implementation science, the liberation of OR from the specialist research and consultancy environment, and co-design of models with service users. Operational research is a mature discipline that has developed a significant volume of methodology to improve health services. OR offers implementation scientists the opportunity to do more upfront system thinking before committing resources or taking risks. OR has three roles within implementation science: structuring an implementation problem, prospective evaluation of implementation problems, and a tool for strategic reconfiguration of health services. Challenges facing OR as implementation science include limited evidence and evaluation of impact, limited service user involvement, a lack of managerial awareness, effective communication between research users and OR modellers, and availability of healthcare data. To progress the science, a focus is needed in three key areas: evaluation of OR interventions, embedding the knowledge of OR in health services, and educating OR modellers about the aims and benefits of service user involvement.

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Research priorities to improve stroke outcomes.

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Research priorities to improve stroke outcomes.

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