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      A cluster randomized trial of a multifaceted quality improvement intervention in Brazilian intensive care units: study protocol

      , The CHECKLIST-ICU Investigators and the BRICNet

      Implementation Science : IS

      BioMed Central

      Intensive care, Critical illness, Intensive care units, Checklist, Hospital mortality, Outcome and process assessment (health care), Quality improvement

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          The uptake of evidence-based therapies in the intensive care environment is suboptimal, particularly in limited-resource countries. Checklists, daily goal assessments, and clinician prompts may improve compliance with best practice processes of care and, in turn, improve clinical outcomes. However, the available evidence on the effectiveness of checklists is unreliable and inconclusive, and the mechanisms are poorly understood. We aim to evaluate whether the use of a multifaceted quality improvement intervention, including the use of a checklist and the definition of daily care goals during multidisciplinary daily rounds and clinician prompts, can improve the in-hospital mortality of patients admitted to intensive care units (ICUs). Our secondary objectives are to assess the effects of the study intervention on specific processes of care, clinical outcomes, and the safety culture and to determine which factors (the processes of care and/or safety culture) mediate the effect of the study intervention on mortality.


          This is a cluster randomized trial involving 118 ICUs in Brazil conducted in two phases. In the observational preparatory phase, we collect baseline data on processes of care and clinical outcomes from 60 consecutive patients with lengths of ICU stay longer than 48 h and apply the Safety Attitudes Questionnaire (SAQ) to 75% or more of the health care staff in each ICU. In the randomized phase, we assign ICUs to the experimental or control arm and repeat data collection. Experimental arm ICUs receive the multifaceted quality improvement intervention, including a checklist and definition of daily care goals during daily multidisciplinary rounds, clinician prompting, and feedback on rates of adherence to selected care processes. Control arm ICUs maintain usual care. The primary outcome is in-hospital mortality, truncated at 60 days. Secondary outcomes include the rates of adherence to appropriate care processes, rates of other clinical outcomes, and scores on the SAQ domains. Analysis follows the intention-to-treat principle, and the primary outcome is analyzed using mixed effects logistic regression.


          This is a large scale, pragmatic cluster-randomized trial evaluating whether a multifaceted quality improvement intervention, including checklists applied during the multidisciplinary daily rounds and clinician prompting, can improve the adoption of proven therapies and decrease the mortality of critically ill patients. If this study finds that the intervention reduces mortality, it may be widely adopted in intensive care units, even those in limited-resource settings.

          Trial registration


          Electronic supplementary material

          The online version of this article (doi:10.1186/s13012-014-0190-0) contains supplementary material, which is available to authorized users.

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          Most cited references 33

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          Grading quality of evidence and strength of recommendations.

          Users of clinical practice guidelines and other recommendations need to know how much confidence they can place in the recommendations. Systematic and explicit methods of making judgments can reduce errors and improve communication. We have developed a system for grading the quality of evidence and the strength of recommendations that can be applied across a wide range of interventions and contexts. In this article we present a summary of our approach from the perspective of a guideline user. Judgments about the strength of a recommendation require consideration of the balance between benefits and harms, the quality of the evidence, translation of the evidence into specific circumstances, and the certainty of the baseline risk. It is also important to consider costs (resource utilisation) before making a recommendation. Inconsistencies among systems for grading the quality of evidence and the strength of recommendations reduce their potential to facilitate critical appraisal and improve communication of these judgments. Our system for guiding these complex judgments balances the need for simplicity with the need for full and transparent consideration of all important issues.
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            GRADE guidelines: 3. Rating the quality of evidence.

            This article introduces the approach of GRADE to rating quality of evidence. GRADE specifies four categories-high, moderate, low, and very low-that are applied to a body of evidence, not to individual studies. In the context of a systematic review, quality reflects our confidence that the estimates of the effect are correct. In the context of recommendations, quality reflects our confidence that the effect estimates are adequate to support a particular recommendation. Randomized trials begin as high-quality evidence, observational studies as low quality. "Quality" as used in GRADE means more than risk of bias and so may also be compromised by imprecision, inconsistency, indirectness of study results, and publication bias. In addition, several factors can increase our confidence in an estimate of effect. GRADE provides a systematic approach for considering and reporting each of these factors. GRADE separates the process of assessing quality of evidence from the process of making recommendations. Judgments about the strength of a recommendation depend on more than just the quality of evidence. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Research Institute - Hospital do Coração (IEP– HCor), Rua Abílio Soares 250, 12th floor, CEP: 04005-000 - São Paulo SP, Brazil
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central (London )
                13 January 2015
                13 January 2015
                : 10
                © Cavalcanti et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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