Lena Schmidt, Ian Cree, Fiona Campbell, WCT EVI MAP group
{"title":"支持系统评审过程的数字工具:介绍","authors":"Lena Schmidt, Ian Cree, Fiona Campbell, WCT EVI MAP group","doi":"10.1111/jep.70100","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Aim</h3>\n \n <p>This article introduces digital tools designed to enhance systematic review processes, emphasizing their functionality, availability, and independent validation in peer-reviewed literature.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>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.</p>\n </section>\n </div>","PeriodicalId":15997,"journal":{"name":"Journal of evaluation in clinical practice","volume":"31 3","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jep.70100","citationCount":"0","resultStr":"{\"title\":\"Digital Tools to Support the Systematic Review Process: An Introduction\",\"authors\":\"Lena Schmidt, Ian Cree, Fiona Campbell, WCT EVI MAP group\",\"doi\":\"10.1111/jep.70100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Aim</h3>\\n \\n <p>This article introduces digital tools designed to enhance systematic review processes, emphasizing their functionality, availability, and independent validation in peer-reviewed literature.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":15997,\"journal\":{\"name\":\"Journal of evaluation in clinical practice\",\"volume\":\"31 3\",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jep.70100\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of evaluation in clinical practice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jep.70100\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of evaluation in clinical practice","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jep.70100","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Digital Tools to Support the Systematic Review Process: An Introduction
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.
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.