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Schmidt L, Sinyor M, Webb RT, Marshall C, Knipe D, Eyles EC, John A, Gunnell D, Higgins JPT. A narrative review of recent tools and innovations toward automating living systematic reviews and evidence syntheses. Z Evid Fortbild Qual Gesundhwes 2023; 181:65-75. [PMID: 37596160 DOI: 10.1016/j.zefq.2023.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 06/19/2023] [Accepted: 06/25/2023] [Indexed: 08/20/2023]
Abstract
Living reviews are an increasingly popular research paradigm. The purpose of a 'living' approach is to allow rapid collation, appraisal and synthesis of evolving evidence on an important research topic, enabling timely influence on patient care and public health policy. However, living reviews are time- and resource-intensive. The accumulation of new evidence and the possibility of developments within the review's research topic can introduce unique challenges into the living review workflow. To investigate the potential of software tools to support living systematic or rapid reviews, we present a narrative review informed by an examination of tools contained on the Systematic Review Toolbox website. We identified 11 tools with relevant functionalities and discuss the important features of these tools with respect to different steps of the living review workflow. Four tools (NestedKnowledge, SWIFT-ActiveScreener, DistillerSR, EPPI-Reviewer) covered multiple, successive steps of the review process, and the remaining tools addressed specific components of the workflow, including scoping and protocol formulation, reference retrieval, automated data extraction, write-up and dissemination of data. We identify several ways in which living reviews can be made more efficient and practical. Most of these focus on general workflow management, or automation through artificial intelligence and machine-learning, in the screening process. More sophisticated uses of automation mostly target living rapid reviews to increase the speed of production or evidence maps to broaden the scope of the map. We use a case study to highlight some of the barriers and challenges to incorporating tools into the living review workflow and processes. These include increased workload, the need for organisation, ensuring timely dissemination and challenges related to the development of bespoke automation tools to facilitate the review process. We describe how current end-user tools address these challenges, and which knowledge gaps remain that could be addressed by future tool development. Dedicated web presences for automatic dissemination of in-progress evidence updates, rather than solely relying on peer-reviewed journal publications, help to make the effort of a living evidence synthesis worthwhile. Despite offering basic living review functionalities, existing end-user tools could be further developed to be interoperable with other tools to support multiple workflow steps seamlessly, to address broader automatic evidence retrieval from a larger variety of sources, and to improve dissemination of evidence between review updates.
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Affiliation(s)
- Lena Schmidt
- National Institute for Health and Care Research Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle, UK; Sciome LLC, Research Triangle Park, North Carolina, USA.
| | - Mark Sinyor
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Roger T Webb
- Division of Psychology and Mental Health, The University of Manchester, Manchester, UK; National Institute for Health and Care Research Greater Manchester Patient Safety Translational Research Centre (NIHR GM PSTRC), Manchester, UK
| | | | - Duleeka Knipe
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emily C Eyles
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; The National Institute of Health and Care Research Applied Research Collaboration West (NIHR ARC West), University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Ann John
- Population Data Science, Swansea University, Swansea, UK; Public Health Wales NHS Trust, Wales, UK
| | - David Gunnell
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; The National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Julian P T Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; The National Institute of Health and Care Research Applied Research Collaboration West (NIHR ARC West), University Hospitals Bristol NHS Foundation Trust, Bristol, UK; The National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
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