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      Research versus practice in quality improvement? Understanding how we can bridge the gap

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          Abstract

          The gap between implementers and researchers of quality improvement (QI) has hampered the degree and speed of change needed to reduce avoidable suffering and harm in health care. Underlying causes of this gap include differences in goals and incentives, preferred methodologies, level and types of evidence prioritized and targeted audiences. The Salzburg Global Seminar on ‘Better Health Care: How do we learn about improvement?’ brought together researchers, policy makers, funders, implementers, evaluators from low-, middle- and high-income countries to explore how to increase the impact of QI. In this paper, we describe some of the reasons for this gap and offer suggestions to better bridge the chasm between researchers and implementers. Effectively bridging this gap can increase the generalizability of QI interventions, accelerate the spread of effective approaches while also strengthening the local work of implementers. Increasing the effectiveness of research and work in the field will support the knowledge translation needed to achieve quality Universal Health Coverage and the Sustainable Development Goals.

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          Adaptive trial designs: a review of barriers and opportunities

          Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice.
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            Strengthening health systems through embedded research

            Realizing the health-related sustainable development goals (SDGs) requires integrated action on system-wide challenges. To address gaps in health service delivery, we need evidence on which government agencies, research institutions, donors and civil society can act. 1 Unless research is relevant to specific health systems, the evidence that it generates can be dismissed by policy-makers. 2 For example, there is plenty of evidence for the effectiveness of standard interventions to prevent maternal and child deaths, but countries vary widely in the degree to which these interventions have been implemented. 3 We argue that embedding of research in real world policy, practice and implementation is needed to strengthen health systems worldwide. Embedded research conducted in partnership with policy-makers and implementers, integrated in different health system settings and that takes into account context-specific factors can ensure greater relevance in policy priority-setting and decision-making. 4 Collaboration between researchers, implementers and policy-makers has been shown to improve uptake of health systems research. 5 However, in many places, prioritization and conduct of research is often done solely by academics. 6 Health research is also largely focused on biomedical and clinical interventions, while health systems and implementation research remains underfunded globally. 7 Often, knowledge translation is an add-on activity after the completion of research projects. The World Health Organization’s report, Changing mindsets: strategy on health policy and systems research, called for the embedding of research into health systems processes. 6 This report explained that when embedding happens, researchers and decision-makers are linked through a system in which the need for evidence to inform policy is understood by decision-makers. The Alliance for Health Policy and Systems Research (AHPSR) and the United Nations Children’s Fund (UNICEF) developed a model for implementation research that addresses research priorities identified by decision-makers and specific challenges of local health systems. 8 In this model, policy-makers and implementers at different levels in the health system are engaged as co-investigators and are involved in all phases of a research project. The approach is meant to enhance policy-makers’ and implementers’ ownership of health systems and policy research. The collaboration is designed to prioritize research on empirical questions of local relevance, generate feasible recommendations and integrate evidence into policy-making and health system strengthening. Policy-makers, implementers and researchers are increasingly keen to collaborate on the design and conduct of research to ensure that it contributes to health policy-making. 9 , 10 Since 2013, AHPSR, UNICEF and Gavi, the Vaccine Alliance, have supported 26 embedded research projects in 15 low- and middle-income countries. These projects aim to foster a better understanding of health systems implementation issues linked to maternal, newborn and child health policies and programmes. 11 Through its African Health Initiative, the Doris Duke Charitable Foundation is also supporting embedded research that aims to enhance the performance of health systems in Africa. 12 In these contexts, embedding research in local health systems helped address real concerns of implementers and supports action to alleviate implementation barriers. Our experience is consistent with evidence showing that embedded research facilitates the integration of scientific findings in policy implementation and health systems strengthening. 13 However, few resources are available to support this approach. We advocate for the embedding of locally-relevant and demand-driven research in health systems worldwide to improve the implementation and scale-up of health policies, thus contributing to achievement of the health-related SDGs.
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              Towards a common terminology: a simplified framework of interventions to promote and integrate evidence into health practices, systems, and policies

              Background A wide range of diverse and inconsistent terminology exists in the field of knowledge translation. This limits the conduct of evidence syntheses, impedes communication and collaboration, and undermines knowledge translation of research findings in diverse settings. Improving uniformity of terminology could help address these challenges. In 2012, we convened an international working group to explore the idea of developing a common terminology and an overarching framework for knowledge translation interventions. Findings Methods included identifying and summarizing existing frameworks, mapping together a subset of those frameworks, and convening a multi-disciplinary group to begin working toward consensus. The group considered four potential approaches to creating a simplified framework: melding existing taxonomies, creating a framework of intervention mechanisms rather than intervention strategies, using a consensus process to expand one of the existing models/frameworks used by the group, or developing a new consensus framework. Conclusions The work group elected to draft a new, simplified consensus framework of interventions to promote and integrate evidence into health practices, systems and policies. The framework will include four key components: strategies and techniques (active ingredients), how they function (causal mechanisms), how they are delivered (mode of delivery), and what they aim to change (intended targets). The draft framework needs to be further developed by feedback and consultation with the research community and tested for usefulness through application and evaluation.
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                Author and article information

                Journal
                Int J Qual Health Care
                Int J Qual Health Care
                intqhc
                International Journal for Quality in Health Care
                Oxford University Press
                1353-4505
                1464-3677
                April 2018
                20 April 2018
                20 April 2018
                : 30
                : Suppl 1 , Salzburg Global Seminar Session 565 - Better Health Care: How do we learn about improvement?
                : 24-28
                Affiliations
                [1 ]Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
                [2 ]Department of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina, 4107 McGavran-Greenberg Hall, CB #7469, Chapel Hill, NC 27599, USA
                [3 ]Department of Hospital Administration, Post Graduate Institute of Medical Education and Research, OPD Block Sector 12, Chandigarh 160012, India
                [4 ]Department of Psychology, University of South Carolina, 1512 pendleton st, Columbia, SC 29208, USA
                [5 ]AcademyHealth, 1666 K Street, Suite 1100, Washington, DC 20006, USA
                [6 ]Department of Health Care Quality and Patient Safety, Institute for Clinical Effectiveness and Health Policy, Dr. Emilio Ravignani 2024 (C1414CPV), Buenos Aires, Argentina
                Author notes
                Address reprint requests to: Lisa R Hirschhorn, Department of Medical Social Sciences, 625 N Michigan Ave 14-013, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA. Tel: 312-503-1797; E-mail: Lisa.Hirschhorn@ 123456Northwestern.edu
                Article
                mzy018
                10.1093/intqhc/mzy018
                5909640
                29447351
                a08b30a2-56ab-4d57-ac99-02b9f7c239aa
                © The Author(s) 2018. Published by Oxford University Press in association with the International Society for Quality in Health Care.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 27 August 2017
                : 17 January 2018
                : 5 February 2018
                Page count
                Pages: 5
                Categories
                Perspectives on Quality

                Medicine
                improvement,learning,complex adaptive systems,implementation,improvement science
                Medicine
                improvement, learning, complex adaptive systems, implementation, improvement science

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