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An optimal search filter for retrieving systematic reviews and meta-analyses
Edwin Lee1, Maureen Dobbins, Kara Decorby
1Faculty of Health Sciences, McMaster University, 1200 Main St, W, Hamilton, ON, Canada.
BMC Medical Research Methodology
|April 20, 2012
Summary
The health-evidence.ca Systematic Review search filter effectively identifies systematic reviews on public health interventions. It maintains high sensitivity while reducing the number of articles needing review, saving time and resources.
Area of Science:
- Health Sciences
- Information Science
Background:
- Health-evidence.ca is an online registry of systematic reviews on public health interventions.
- Keeping the registry updated requires extensive bibliographic database searching.
- Search filters aid in identifying relevant literature, categorized by content or study design.
Purpose of the Study:
- To develop and validate the health-evidence.ca Systematic Review search filter.
- To compare the performance of this filter against other systematic review search filters.
Main Methods:
- Conducted analysis of 31 search filters across MEDLINE, EMBASE, and CINAHL.
- Evaluated filter performance using a validation dataset (219 articles, Jan 2004-Dec 2005).
- Assessed sensitivity, specificity, precision, and number needed to read for each filter.
Main Results:
- Nineteen of 31 filters achieved >85% sensitivity.
- Most high-sensitivity filters compromised precision, resulting in large retrieval sets.
- The health-evidence.ca filter maintained sensitivity while significantly reducing the number needed to screen.
Conclusions:
- The health-evidence.ca Systematic Review search filter is valuable for identifying systematic reviews on public health interventions.
- This filter streamlines updates for the health-evidence.ca registry.
- It offers time and resource savings without sacrificing the sensitivity of literature retrieval.
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