Scott Anna Mae, Forbes Connor, Clark Justin, Carter Matt, Glasziou Paul, Munn Zachary
Institute for Evidence-Based Healthcare, Bond University, Gold Coast, Australia.
Institute for Evidence-Based Healthcare, Bond University, Gold Coast, Australia.
J Clin Epidemiol. 2021 Oct;138:80-94. doi: 10.1016/j.jclinepi.2021.06.030. Epub 2021 Jul 7.
We investigated systematic review automation tool use by systematic reviewers, health technology assessors and clinical guideline developerst.
An online, 16-question survey was distributed across several evidence synthesis, health technology assessment and guideline development organizations. We asked the respondents what tools they use and abandon, how often and when do they use the tools, their perceived time savings and accuracy, and desired new tools. Descriptive statistics were used to report the results.
A total of 253 respondents completed the survey; 89% have used systematic review automation tools - most frequently whilst screening (79%). Respondents' "top 3" tools included: Covidence (45%), RevMan (35%), Rayyan and GRADEPro (both 22%); most commonly abandoned were Rayyan (19%), Covidence (15%), DistillerSR (14%) and RevMan (13%). Tools saved time (80%) and increased accuracy (54%). Respondents taught themselves to how to use the tools (72%); lack of knowledge was the most frequent barrier to tool adoption (51%). New tool development was suggested for the searching and data extraction stages.
Automation tools will likely have an increasingly important role in high-quality and timely reviews. Further work is required in training and dissemination of automation tools and ensuring they meet the desirable features of those conducting systematic reviews.
我们调查了系统评价者、卫生技术评估者和临床指南开发者对系统评价自动化工具的使用情况。
通过在线方式向多个证据综合、卫生技术评估和指南制定组织发放了一份包含16个问题的调查问卷。我们询问了受访者使用和放弃的工具、使用工具的频率和时间、他们认为节省的时间和准确性,以及期望的新工具。采用描述性统计报告结果。
共有253名受访者完成了调查;89%的人使用过系统评价自动化工具——最常在筛选时使用(79%)。受访者“排名前三”的工具包括:Covidence(45%)、RevMan(35%)、Rayyan和GRADEPro(均为22%);最常被放弃的是Rayyan(19%)、Covidence(15%)、DistillerSR(14%)和RevMan(13%)。工具节省了时间(80%)并提高了准确性(54%)。受访者自学如何使用工具(72%);缺乏知识是采用工具最常见的障碍(51%)。有人建议在检索和数据提取阶段开发新工具。
自动化工具在高质量和及时的评价中可能会发挥越来越重要的作用。在自动化工具的培训和推广以及确保它们满足进行系统评价者的期望特征方面,还需要进一步开展工作。