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Automated tools for evidence quality assessment: a scoping review.
Jiayi Huang1,2,3, Xinxin Deng4, Liying Zhou5
1Health Technology Assessment Center/Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, 199 Donggang West Road, Lanzhou, 730000, China.
BMC Medical Research Methodology
|June 16, 2026
Summary
Automated tools for evidence quality assessment can improve efficiency but are often limited to clinical trials and require human oversight. Further validation is needed for broader public health use.
Area of Science:
- Public Health
- Health Informatics
- Evidence-Based Practice
Background:
- Manual evidence quality assessment is time-consuming and variable.
- Automated tools offer potential for improved efficiency and consistency.
- A comprehensive map of these tools is currently lacking.
Purpose of the Study:
- To systematically map the characteristics, performance, and limitations of automated evidence quality assessment tools.
- To identify existing tools and their development status.
Main Methods:
- Systematic literature search of 10 databases (English and Chinese) up to February 2025.
- Inclusion of original research on tool development, application, or validation.
- Descriptive synthesis of study and tool characteristics (e.g., design, type, features, reliability, validity).
Main Results:
- Twenty studies identified, primarily from the UK, Canada, and Australia.
- Observational designs (75%) predominated over randomized controlled trials (10%).
- Twelve distinct tools were identified; 65% were publicly available, but 50% required human oversight and were often tailored for clinical trials.
Conclusions:
- Automated tools show promise for enhancing efficiency and consistency in evidence quality assessment.
- Current tools have limited applicability, often requiring human supervision and focusing on clinical trials.
- Broader adaptation and rigorous validation are necessary for integration into public health decision-making.
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