336 research outputs found

    Methodology Issues in Implementation Science

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    Background: Putting evidence into practice at the point of care delivery requires an understanding of implementation strategies that work, in what context and how. Objective: To identify methodological issues in implementation science using 4 studies as cases and make recommendations for further methods development. Research Design: Four cases are presented and methodological issues identified. For each issue raised, evidence on the state of the science is described. Results: Issues in implementation science identified include diverse conceptual frameworks, potential weaknesses in pragmatic study designs, and the paucity of standard concepts and measurement. Conclusions: Recommendations to advance methods in implementation include developing a core set of implementation concepts and metrics, generating standards for implementation methods including pragmatic trials, mixed methods designs, complex interventions and measurement, and endorsing reporting standards for implementation studies

    Variations in Institutional Review Board Approval in the Implementation of an Improvement Research Study

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    The purpose of this paper is to report the variance in institutional review board (IRB) reviews as part of the implementation of a multisite, quality improvement study through the Improvement Science Research Network (ISRN) and recommend strategies successful in procuring timely IRB approval. Using correspondence documents as data sources, the level of review was identified and time to submission, time to approval, and time to study start were analyzed. Thirteen of the 14 IRBs conducted independent reviews of the project. Twelve IRBs approved the study through expedited review while two IRBs reviewed the project at a full board meeting. Lastly, 11 of the 14 sites required documented consent. The greatest delay in approval was seen early on in the IRB process with site PIs averaging 45.1 ± 31.8 days to submit the study to the IRB. IRB approvals were relatively quick with an average of 14 ± 5.7 days to approval. The delay in study submission may be attributed to a lack of clear definitions and differing interpretations of the regulations that challenge researchers

    Adopting Best Practices from Team Science in a Healthcare Improvement Research Network: The Impact on Dissemination and Implementation

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    Healthcare is a complex adaptive system, and efforts to improve through the implementation of best practice are well served by various interacting disciplines within the system. As a transdisciplinary model is new to clinicians, an infrastructure that creates academic-practice partnerships and builds capacity for scientific collaboration is necessary to test, spread, and implement improvement strategies. This paper describes the adoption of best practices from the science of team science in a healthcare improvement research network and the impact on conducting a large-scale network study. Key components of the research network infrastructure were mapped to a team science framework and evaluated in terms of their effectiveness and impact on a national study of nursing operations. Results from this study revealed an effective integration of the team science principles which facilitated the rapid collection of a large dataset. Implications of this study support a collaborative model for improvement research and stress a need for future research and funding to further evaluate the impact on dissemination and implementation

    Real-Time Reporting of Small Operational Failures in Nursing Care

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    Addressing microsystem problems from the frontline holds promise for quality enhancement. Frontline providers are urged to apply quality improvement; yet no systematic approach to problem detection has been tested. This study investigated a self-report approach to detecting operational failures encountered during patient care. Methods. Data were collected from 5 medical-surgical units over 4 weeks. Unit staff documented operational failures on a small distinctive Pocket Card. Frequency distributions for the operational failures in each category were calculated for each hospital overall and disaggregated by shift. Rate of operational failures on each unit was also calculated. Results. A total of 160 nurses participated in this study reporting a total of 2,391 operational failures over 429 shifts. Mean number of problems per shift varied from 4.0 to 8.5 problems with equipment/supply problems being the most commonly reported category. Conclusions. Operational failures are common on medical-surgical clinical units. It is feasible for unit staff to record these failures in real time. Many types of failures were recognized by frontline staff. This study provides preliminary evidence that the Pocket Card is a feasible approach to detecting operational failures in real time. Continued research on methodologies to investigate the impact of operational failures is warranted

    Teaching for implementation: A framework for building implementation research and practice capacity within the translational science workforce

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    Implementation science offers a compelling value proposition to translational science. As such, many translational science stakeholders are seeking to recruit, teach, and train an implementation science workforce. The type of workforce that will make implementation happen consists of both implementation researchers and practitioners, yet little guidance exists on how to train such a workforce. We-members of the Advancing Dissemination and Implementation Sciences in CTSAs Working Group-present the Teaching For Implementation Framework to address this gap. We describe the differences between implementation researchers and practitioners and demonstrate what and how to teach them individually and in co-learning opportunities. We briefly comment on educational infrastructures and resources that will be helpful in furthering this type of approach

    Situating dissemination and implementation sciences within and across the translational research spectrum

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    The efficient and effective movement of research into practice is acknowledged as crucial to improving population health and assuring return on investment in healthcare research. The National Center for Advancing Translational Science which sponsors Clinical and Translational Science Awards (CTSA) recognizes that dissemination and implementation (D&I) sciences have matured over the last 15 years and are central to its goals to shift academic health institutions to better align with this reality. In 2016, the CTSA Collaboration and Engagement Domain Task Force chartered a D&I Science Workgroup to explore the role of D&I sciences across the translational research spectrum. This special communication discusses the conceptual distinctions and purposes of dissemination, implementation, and translational sciences. We propose an integrated framework and provide real-world examples for articulating the role of D&I sciences within and across all of the translational research spectrum. The framework\u27s major proposition is that it situates D&I sciences as targeted sub-sciences of translational science to be used by CTSAs, and others, to identify and investigate coherent strategies for more routinely and proactively accelerating research translation. The framework highlights the importance of D&I thought leaders in extending D&I principles to all research stages

    Development of a Novel Renal Activity Index of Lupus Nephritis in Children and Young Adults

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    OBJECTIVE: Noninvasive estimation of the degree of inflammation seen on kidney biopsy with lupus nephritis (LN) remains difficult. The objective of this study was to develop a Renal Activity Index for Lupus (RAIL) that, based solely on laboratory measures, accurately reflects histologic LN activity. METHODS: We assayed traditional LN laboratory tests and 16 urine biomarkers (UBMs) in children (n = 47) at the time of kidney biopsy. Histologic LN activity was measured by the National Institutes of Health activity index (NIH-AI) and the tubulointerstitial activity index (TIAI). High LN-activity status (versus moderate/low) was defined as NIH-AI scores >10 (versus ≤10) or TIAI scores >5 (versus ≤5). RAIL algorithms that predicted LN-activity status for both NIH-AI and TIAI were derived by stepwise multivariate logistic regression, considering traditional biomarkers and UBMs as candidate components. The accuracy of the RAIL for discriminating by LN-activity status was determined. RESULTS: The differential excretion of 6 UBMs (neutrophil gelatinase-associated lipocalin, monocyte chemotactic protein 1, ceruloplasmin, adiponectin, hemopexin, and kidney injury molecule 1) standardized by urine creatinine was considered in the RAIL. These UBMs predicted LN-activity (NIH-AI) status with >92% accuracy and LN-activity (TIAI) status with >80% accuracy. RAIL accuracy was minimally influenced by concomitant LN damage. Accuracies between 71% and 85% were achieved without standardization of the UBMs. The strength of these UBMs to reflect LN-activity status was confirmed by principal component and linear discriminant analyses. CONCLUSION: The RAIL is a robust and highly accurate noninvasive measure of LN activity. The measurement properties of the RAIL, which reflect the degree of inflammatory changes as seen on kidney biopsy, will require independent validation

    Community Health Environment Scan Survey (CHESS): a novel tool that captures the impact of the built environment on lifestyle factors

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    Background: Novel1 1This study was performed on behalf of the Community Interventions for Health (CIH) collaboration. efforts and accompanying tools are needed to tackle the global burden of chronic disease. This paper presents an approach to describe the environments in which people live, work, and play. Community Health Environment Scan Survey (CHESS) is an empirical assessment tool that measures the availability and accessibility, of healthy lifestyle options lifestyle options. CHESS reveals existing community assets as well as opportunities for change, shaping community intervention planning efforts by focusing on community-relevant opportunities to address the three key risk factors for chronic disease (i.e. unhealthy diet, physical inactivity, and tobacco use). Methods: The CHESS tool was developed following a review of existing auditing tools and in consultation with experts. It is based on the social-ecological model and is adaptable to diverse settings in developed and developing countries throughout the world. Results: For illustrative purposes, baseline results from the Community Interventions for Health (CIH) Mexico site are used, where the CHESS tool assessed 583 food stores and 168 restaurants. Comparisons between individual-level survey data from schools and community-level CHESS data are made to demonstrate the utility of the tool in strategically guiding intervention activities. Conclusion: The environments where people live, work, and play are key factors in determining their diet, levels of physical activity, and tobacco use. CHESS is the first tool of its kind that systematically and simultaneously examines how built environments encourage/discourage healthy eating, physical activity, and tobacco use. CHESS can help to design community interventions to prevent chronic disease and guide healthy urban planning
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