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Validation of The Umbrella Collaboration for Tertiary Evidence Synthesis in Geriatrics: Mixed Methods Study
Beltran Carrillo1, Marta Rubinos-Cuadrado1, Jazmin Parellada1
1The Umbrella Collaboration, C/ Ferraz, 49, Madrid, 28008, Spain, 34 637016776.
JMIR Formative Research
|July 8, 2025
Summary
The Umbrella Collaboration (TU) effectively synthesizes tertiary evidence, identifying more outcomes than traditional umbrella reviews (TURs) with comparable results. This AI-assisted method offers a faster, more comprehensive approach to evidence synthesis.
Area of Science:
- Health Services Research
- Medical Informatics
- Evidence-Based Medicine
Background:
- Tertiary evidence synthesis is crucial for healthcare decision-making and policy.
- Traditional umbrella reviews (TURs) are the current standard but can be time-consuming.
- The Umbrella Collaboration (TU) is an innovative, semiautomated methodology for tertiary evidence synthesis.
Purpose of the Study:
- To validate The Umbrella Collaboration (TU) methodology against traditional umbrella reviews (TURs).
- To assess if TU achieves comparable effectiveness to TURs while being more timely, efficient, and comprehensive.
- To evaluate TU's artificial intelligence-assisted, software-driven approach for evidence synthesis.
Main Methods:
- A comparative study matched 8 traditional umbrella reviews (TURs) with parallel projects using The Umbrella Collaboration (TU) in geriatrics.
- Outcomes of interest, effect sizes, certainty ratings, and execution times were systematically compared.
- Statistical analyses included chi-square tests and Spearman correlations to compare quantitative and qualitative metrics.
Main Results:
- TU replicated 85% of outcomes from TURs and identified 4.77 times more additional outcomes.
- Effect size classifications showed 94% concordance, with moderate association (Cramér V=0.339).
- TU projects averaged 4 hours 46 minutes, significantly faster than the estimated 6-12 months for TURs.
Conclusions:
- The Umbrella Collaboration (TU) demonstrates high concordance with traditional umbrella reviews (TURs), validating its effectiveness.
- TU significantly increases the number of identified outcomes and drastically reduces synthesis time.
- TU presents a valid, efficient, scalable, and time-efficient alternative for tertiary evidence synthesis, particularly when rapid results are needed.
Keywords:
AI-assisted synthesisThe Umbrella Collaborationalgorithmsanalyticsartificial intelligencedigital healthdigital interventionsdigital technologyevidence-based decision-makinghealth research methodologymachine learningmodelstertiary evidence synthesisumbrella reviewsMore Related Videos
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