Damiani LP, Cavalcanti AB, Moreira FR, Machado F, Bozza FA, Salluh JIF, Campagnucci VP, Normilio-Silva K, Chiattone VC, Angus DC, Berwanger O, Chou H Chang C. A cluster-randomised trial of a multifaceted quality improvement intervention in Brazilian intensive care units (Checklist-ICU trial): statistical analysis plan.
CRIT CARE RESUSC 2015;
17:113-121. [PMID:
26017129]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
BACKGROUND
The Checklist During Multidisciplinary Visits for Reduction of Mortality in Intensive Care Units (Checklist- ICU) trial is a pragmatic, two-arm, cluster-randomised trial involving 118 intensive care units in Brazil, with the primary objective of determining if a multifaceted qualityimprovement intervention with a daily checklist, definition of daily care goals during multidisciplinary daily rounds and clinician prompts can reduce inhospital mortality.
OBJECTIVE
To describe our trial statistical analysis plan (SAP).
METHODS
This is an ongoing trial conducted in two phases. In the preparatory observational phase, we collect three sets of baseline data: ICU characteristics; patient characteristics, processes of care and outcomes; and completed safety attitudes questionnaires (SAQs). In the randomised phase, ICUs are assigned to the experimental or control arms and we collect patient data and repeat the SAQ.
RESULTS
Our SAP includes the prespecified model for the primary and secondary outcome analyses, which account for the cluster-randomised design and availability of baseline data. We also detail the multiple mediation models that we will use to assess our secondary hypothesis (that the effect of the intervention on inhospital mortality is mediated not only through care processes targeted by the checklist, but also through changes in safety culture). We describe our approach to sensitivity and subgroup analyses and missing data.
CONCLUSION
We report our SAP before closing our study database and starting analysis. We anticipate that this should prevent analysis bias and enhance the utility of results.
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