Abstract
BACKGROUND: The introduction of systematic reviews in medicine has prompted a paradigm shift in employing evidence for decision-making across various fields. Its methodology involves structured comparisons, critical appraisals, and pooled data analysis to inform decision-making. The process itself is resource-intensive and time-consuming which can impede the timely incorporation of the latest evidence into clinical practice. AIM: This article introduces digital tools designed to enhance systematic review processes, emphasizing their functionality, availability, and independent validation in peer-reviewed literature. METHODS: We discuss digital evidence synthesis tools for systematic reviews, identifying tools for all review processes, tools for search strategy development, reference management, study selection, data extraction, and critical appraisal. Emphasis is on validated, functional tools with independently published method evaluations. RESULTS: Tools like EPPI-Reviewer, Covidence, DistillerSR, and JBI-SUMARI provide comprehensive support for systematic reviews. Additional tools cater to evidence search (e.g., PubMed PICO, Trialstreamer), reference management (e.g., Mendeley), prioritization in study selection (e.g., Abstrackr, EPPI-Reviewer, SWIFT-ActiveScreener), and risk bias assessment (e.g., RobotReviewer). Machine learning and AI integration facilitate workflow efficiency but require end-user informed evaluation for their adoption. CONCLUSION: The development of digital tools, particularly those incorporating AI, represents a significant advancement in systematic review methodology. These tools not only support the systematic review process but also have the potential to improve the timeliness and quality of evidence available for decision-making. The findings are relevant to clinicians, researchers, and those involved in the production or support of systematic reviews, with broader applicability to other research methods.