Data extraction
Data extraction involves collecting relevant data elements from studies included in the review and making these data elements available for synthesis. The extracted data should be presented as a table in the final review.
Alert
When undertaking a review, it is crucial to consult the specific review guidelines provided for managing data extraction. These guidelines offer tailored recommendations to ensure the process is thorough and unbiased.
Research data
Research data can be qualitative, quantitative, or a combination of both (mixed methods). The specific data collected from the studies is planned during the protocol stage of your review.
Commonly collected data elements include:
Study title and authors
Country where the study was conducted
Population details
Study results
Other details relevant to research question
Data extraction process
To minimise bias the data extraction process should be meticulously planned, piloted, and documented in the protocol stage of your review. To further reduce bias, it is recommended that at least two reviewers complete this stage with a plan to resolve any discrepancy, similar to the screening stage. The data extraction process should also be reported in the final review for transparency.
Data extraction software
Software is available to support data extraction. Some review teams design their own data collection forms using other software. Screening tools such as LitQuest and Covidence have data extraction functionality.