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      A science of collaborative learning health systems

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          Abstract

          Introduction

          Improving the U.S. healthcare system and health outcomes is one of the most pressing public health challenges of our time. Previously described Collaborative Learning Health Systems (CLHSs) are a promising approach to outcomes improvement. In order to fully realize this promise, a deeper understanding of this phenomenon is necessary.

          Methods

          We drew on our experience over the past decade with CLHSs as well as qualitative literature review to answer three questions: What kind of phenomena are CLHSs? and what is an appropriate scientific approach? How might we frame CLHSs conceptually? What are potential mechanisms of action?

          Results

          CLHSs are complex adaptive systems in which all stakeholders are able to collaborate, at scale, to create and share resources to satisfy a variety of needs. This is accomplished by providing infrastructure and services that enable stakeholders to act on their inherent motivations. This framing has implications for both research and practice.

          Conclusion

          Articulating this framework and potential mechanisms of action should facilitate research to test and refine hypotheses as well as guide practice to develop and optimize this promising approach to improving healthcare systems.

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          Most cited references60

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          Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact.

          This study proposes methods for blending design components of clinical effectiveness and implementation research. Such blending can provide benefits over pursuing these lines of research independently; for example, more rapid translational gains, more effective implementation strategies, and more useful information for decision makers. This study proposes a "hybrid effectiveness-implementation" typology, describes a rationale for their use, outlines the design decisions that must be faced, and provides several real-world examples. An effectiveness-implementation hybrid design is one that takes a dual focus a priori in assessing clinical effectiveness and implementation. We propose 3 hybrid types: (1) testing effects of a clinical intervention on relevant outcomes while observing and gathering information on implementation; (2) dual testing of clinical and implementation interventions/strategies; and (3) testing of an implementation strategy while observing and gathering information on the clinical intervention's impact on relevant outcomes. The hybrid typology proposed herein must be considered a construct still in evolution. Although traditional clinical effectiveness and implementation trials are likely to remain the most common approach to moving a clinical intervention through from efficacy research to public health impact, judicious use of the proposed hybrid designs could speed the translation of research findings into routine practice.
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            Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention

            Across two studies with more than 1,700 U.S. adults recruited online, we present evidence that people share false claims about COVID-19 partly because they simply fail to think sufficiently about whether or not the content is accurate when deciding what to share. In Study 1, participants were far worse at discerning between true and false content when deciding what they would share on social media relative to when they were asked directly about accuracy. Furthermore, greater cognitive reflection and science knowledge were associated with stronger discernment. In Study 2, we found that a simple accuracy reminder at the beginning of the study (i.e., judging the accuracy of a non-COVID-19-related headline) nearly tripled the level of truth discernment in participants’ subsequent sharing intentions. Our results, which mirror those found previously for political fake news, suggest that nudging people to think about accuracy is a simple way to improve choices about what to share on social media.
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              Organizing care for patients with chronic illness.

              Usual medical care often fails to meet the needs of chronically ill patients, even in managed, integrated delivery systems. The medical literature suggests strategies to improve outcomes in these patients. Effective interventions tend to fall into one of five areas: the use of evidence-based, planned care; reorganization of practice systems and provider roles; improved patient self-management support; increased access to expertise; and greater availability of clinical information. The challenge is to organize these components into an integrated system of chronic illness care. Whether this can be done most efficiently and effectively in primary care practice rather than requiring specialized systems of care remains unanswered.
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                Author and article information

                Contributors
                michael.seid@cchmc.org
                Journal
                Learn Health Syst
                Learn Health Syst
                10.1002/(ISSN)2379-6146
                LRH2
                Learning Health Systems
                John Wiley and Sons Inc. (Hoboken )
                2379-6146
                01 June 2021
                July 2021
                : 5
                : 3 , Collaborative learning health systems: Science and practice ( doiID: 10.1002/lrh2.v5.3 )
                : e10278
                Affiliations
                [ 1 ] Division of Pulmonary Medicine Cincinnati Children's Hospital Medical Center Cincinnati Ohio USA
                [ 2 ] Cincinnati Children's Hospital, James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center Cincinnati Ohio USA
                [ 3 ] Department of Pediatrics College of Medicine, University of Cincinnati Cincinnati Ohio USA
                Author notes
                [*] [* ] Correspondence

                Michael Seid, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.

                Email: michael.seid@ 123456cchmc.org

                Author information
                https://orcid.org/0000-0001-9773-9263
                https://orcid.org/0000-0003-2589-2538
                Article
                LRH210278
                10.1002/lrh2.10278
                8278442
                34277944
                6f7889f1-e0b3-4b53-8baf-6db01945b7e1
                © 2021 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 12 May 2021
                : 10 December 2020
                : 13 May 2021
                Page count
                Figures: 1, Tables: 0, Pages: 8, Words: 6860
                Categories
                Commentary
                Commentaries
                Custom metadata
                2.0
                July 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.4 mode:remove_FC converted:14.07.2021

                collaborative learning health systems,science of learning health systems,systems science,theoretical framework

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