Rationale and design of a cluster-randomized multifaceted intervention trial to improve stroke care quality in China: The GOLDEN BRIDGE-Acute Ischemic Stroke
© 2015 Elsevier Inc. All rights reserved. Background Prior studies have demonstrated a significant gap between guideline-based recommendations and clinical practice in the management of acute ischemic stroke (AIS) in China. Aims This study implements a targeted multifaceted quality improvement intervention in AIS patients and identifies the feasibility and efficacy of this intervention. Design This is a multicenter, 2-arm, open-label, cluster-randomized trial involving 40 clusters (hospitals) from China National Network of Stroke Research. Hospitals are randomized to receive a targeted multifaceted quality improvement intervention (experimental group) or routine standard of care (control group). The multifaceted intervention includes an evidence-based clinical pathway, written care protocols, a quality coordinator, and a monitoring and feedback system of performance measures. The number of enrolled patients in the trial will be 4,800. Primary outcome is the measure of the adherence to AIS evidence-based performance measures including the composite measure (defined as the total number of interventions performed among eligible patients divided by the total number of possible interventions among eligible patients) and the all-or-none measure (defined as the proportion of eligible patients who receive all of the performance measure interventions for which they are eligible). Secondary patient outcomes include inhospital death; a new vascular event; disability; and all-cause death at 3, 6, and 12 months after initial symptom onset. All analyses will be performed according to the intention-to-treatment principle and accounted for clustering using generalized estimating equations. Conclusions If proven effective, this targeted multifaceted intervention model will be extended nationwide as a model to bridge the evidence-based gap in the AIS management in China.
Wang, Y; Li, Z; Xian, Y; Zhao, X; Li, H; Shen, H; Wang, C; Liu, L; Pan, Y; Wang, D; Prvu Bettger, J; Fonarow, GC; Schwamm, LH; Smith, SC; Peterson, ED
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