Digital Tools to Support the Systematic Review Process: An Introduction

IF 2.1 4区医学 Q3 HEALTH CARE SCIENCES & SERVICES

Journal of evaluation in clinical practice Pub Date : 2025-04-28 DOI:10.1111/jep.70100

Lena Schmidt, Ian Cree, Fiona Campbell, WCT EVI MAP group

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引用次数: 0

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.

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支持系统评审过程的数字工具：介绍

医学系统评价的引入促进了在各个领域采用证据进行决策的范式转变。其方法包括结构化比较、批判性评估和汇总数据分析，为决策提供信息。该过程本身是资源密集型和耗时的，这可能妨碍将最新证据及时纳入临床实践。本文介绍了旨在加强系统评审过程的数字工具，强调了它们在同行评审文献中的功能、可用性和独立验证。方法我们讨论了用于系统评价的数字证据合成工具、所有评价过程的识别工具、搜索策略开发工具、参考管理工具、研究选择工具、数据提取工具和关键评价工具。重点是经过验证的功能工具和独立发布的方法评估。EPPI-Reviewer、Covidence、DistillerSR和jbi - sumeri等工具为系统评价提供了全面的支持。其他工具用于证据搜索（例如PubMed PICO， Trialstreamer），参考管理（例如Mendeley），研究选择的优先级（例如Abstrackr， EPPI-Reviewer, SWIFT-ActiveScreener）和风险偏差评估（例如RobotReviewer）。机器学习和人工智能集成提高了工作流程的效率，但需要最终用户对其采用进行知情评估。数字工具的发展，特别是那些结合人工智能的工具，代表了系统评价方法的重大进步。这些工具不仅支持系统审查过程，而且有可能提高决策可用证据的及时性和质量。这些发现与临床医生、研究人员以及参与系统评价制作或支持的人员相关，对其他研究方法具有更广泛的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of evaluation in clinical practice 医学-卫生保健

CiteScore

4.80

自引率

4.20%

发文量

143

审稿时长

3-8 weeks

期刊介绍： The Journal of Evaluation in Clinical Practice aims to promote the evaluation and development of clinical practice across medicine, nursing and the allied health professions. All aspects of health services research and public health policy analysis and debate are of interest to the Journal whether studied from a population-based or individual patient-centred perspective. Of particular interest to the Journal are submissions on all aspects of clinical effectiveness and efficiency including evidence-based medicine, clinical practice guidelines, clinical decision making, clinical services organisation, implementation and delivery, health economic evaluation, health process and outcome measurement and new or improved methods (conceptual and statistical) for systematic inquiry into clinical practice. Papers may take a classical quantitative or qualitative approach to investigation (or may utilise both techniques) or may take the form of learned essays, structured/systematic reviews and critiques.