Cutting Edge Or Blunt Instrument: How To Decide If A Stepped Wedge Design Is Right For You

BMJ QUALITY & SAFETY(2021)

引用 12|浏览12
暂无评分
摘要
The last 10 years have seen an extraordinary surge of interest in ‘stepped wedge’ designs for evaluating interventions to improve health and social care. Reviews of published trials and registered protocols have shown an exponential increase in the number of trials citing a stepped wedge approach.1–6 A growing body of work on methods for the design, conduct and analysis of stepped wedge trials has emerged, building on seminal work by Hussey and Hughes in 2007.7 The Consolidated Standards of Reporting Trials reporting guidelines for stepped wedge cluster randomised trials are now available, making it easier for investigators to appraise evidence and plan their own evaluations.8\n\nBut published examples of stepped wedge evaluations in quality improvement illustrate some of the practical challenges. On the one hand, limited research resources may force investigators to stagger implementation at different sites9; on the other hand, persuading sites to follow a precise, predetermined schedule for implementation may be hard.10 In fact, investigators who plan a stepped wedge trial must balance a number of logistical, ethical and methodological issues.11 12 In this article, we focus predominantly on the design of such evaluations, and encourage a questioning approach. We take a ‘trial’ to mean a study involving the prospective, experimental allocation of interventions,13 but more particularly we focus on studies where those allocations are randomised. We start with the question of what is meant by a stepped wedge trial.\n\nThe vast majority of stepped wedge trials are cluster randomised, and when people refer to stepped wedge designs this is usually what they have in mind. A cluster randomised trial is a trial in which all the participants at the same site or ‘cluster’ are allocated to the same intervention.14 Stepped wedge cluster randomised trials are run over an …
更多
查看译文
关键词
accreditation, attitudes, audit and feedback
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要