Systematic review automation technologies

By G. Tsafnat, P. Glasziou, M. K. Choong, A. Dunn, Filippo Galgani, Enrico W. Coiera. Systematic Reviews, 2014

427 citations recorded by the source corpus.

Systematic reviews, a cornerstone of evidence-based medicine, are not produced quickly enough to support clinical practice. The cost of production, availability of the requisite expertise and timeliness are often quoted as major contributors for the delay. This detailed survey of the state of the art of information systems designed to support or automate individual tasks in the systematic review, and in particular systematic reviews of randomized controlled clinical trials, reveals trends that see the convergence of several parallel research projects.We surveyed literature describing informatics systems that support or automate the processes of systematic review or each of the tasks of the systematic review. Several projects focus on automating, simplifying and/or streamlining specific tasks of the systematic review. Some tasks are already fully automated while others are still largely manual. In this review, we describe each task and the effect that its automation would have on the entire systematic review process, summarize the existing information system support for each task, and highlight where further research is needed for realizing automation for the task. Integration of the systems that automate systematic review tasks may lead to a revised systematic review workflow. We envisage the optimized workflow will lead to system in which each systematic review is described as a computer program that automatically retrieves relevant trials, appraises them, extracts and synthesizes data, evaluates the risk of bias, performs meta-analysis calculations, and produces a report in real time.

Subfields: Information Systems and Management, Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5f9e948be446694c925aad687973936cf18571a8

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Citations in the corpus

Fact or Fiction: Verifying Scientific Claims (2020, methodology): “Automated evidence synthesis (Marshall and Wallace, 2019; Beller et al., 2018; Tsafnat et al., 2014; Marshall et al., 2017) seeks to automate the process of creating systematic reviews of the medical literature7 – for instance, by extracting PICO snippets (Nye et al.”
Rayyan—a web and mobile app for systematic reviews (2016, background): “An increasing number of projects are underway which focus on the automation of segments of the systematic review process, and although several tools and software have been developed, so far, none of them span the entire process of review production [5].”
MSˆ2: Multi-Document Summarization of Medical Studies (2021, background): “time and cost of creating and updating reviews has inspired efforts at automation (Tsafnat et al., 2014; Marshall et al., 2016; Beller et al., 2018; Marshall and Wallace, 2019), and the constant deluge of studies3 has only increased this need.”
Using text mining for study identification in systematic reviews: a systematic review of current approaches (2015, background): “The use of automation to assist in study selection is possibly the most advanced of all the areas where automation in systematic reviews is being developed; but others range from writing sections of the report, formulating the review question and automated data extraction and quality assessment [90-”
Cochrane Rapid Reviews Methods Group offers evidence-informed guidance to conduct rapid reviews (2020, positive): “However, the methodological rigor and process that makes SR evidence trustworthy often take one to 2 years to complete [1 e 4] and limit their utility to meet the time-sensitive needs of stakeholders.”
Automation of systematic literature reviews: A systematic literature review (2021, background): “Tsafnat et al. [21] describe each step in the systematic review process, its automation potential, and current tools that have already been developed.”