Systematic review automation tools improve efficiency but lack of knowledge impedes their adoption: a survey.
J Clin Epidemiol
; 138: 80-94, 2021 10.
Article
in English
| MEDLINE | ID: covidwho-1454254
ABSTRACT
OBJECTIVE:
We investigated systematic review automation tool use by systematic reviewers, health technology assessors and clinical guideline developerst. STUDY DESIGN ANDSETTING:
An online, 16-question survey was distributed across several evidence synthesis, health technology assessment and guideline development organizations. We asked the respondents what tools they use and abandon, how often and when do they use the tools, their perceived time savings and accuracy, and desired new tools. Descriptive statistics were used to report the results.RESULTS:
A total of 253 respondents completed the survey; 89% have used systematic review automation tools - most frequently whilst screening (79%). Respondents' "top 3" tools included Covidence (45%), RevMan (35%), Rayyan and GRADEPro (both 22%); most commonly abandoned were Rayyan (19%), Covidence (15%), DistillerSR (14%) and RevMan (13%). Tools saved time (80%) and increased accuracy (54%). Respondents taught themselves to how to use the tools (72%); lack of knowledge was the most frequent barrier to tool adoption (51%). New tool development was suggested for the searching and data extraction stages.CONCLUSION:
Automation tools will likely have an increasingly important role in high-quality and timely reviews. Further work is required in training and dissemination of automation tools and ensuring they meet the desirable features of those conducting systematic reviews.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Research Personnel
/
Automation
/
Technology Assessment, Biomedical
/
Attitude to Computers
/
Systematic Reviews as Topic
Type of study:
Observational study
/
Prognostic study
/
Reviews
/
Systematic review/Meta Analysis
Limits:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Language:
English
Journal:
J Clin Epidemiol
Journal subject:
Epidemiology
Year:
2021
Document Type:
Article
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