Data extraction is the process of extracting the relevant pieces of information from the studies you have assessed for eligibility in your review and organizing the information in a way that will help you synthesize the studies and draw conclusions.
Extracting data from reviewed studies should be done in accordance to pre-established guidelines, such as the ones from PRISMA. From each included study, the following data may need to be extracted, depending on the review's purpose: title, author, year, journal, research question and specific aims, conceptual framework, hypothesis, research methods or study type, and concluding points. Special attention should be paid to the methodology, in order to organize studies by study type category in the review results section. If a meta-analysis is also being completed, extract raw and refined data from each result in the study.
Established frameworks for extracting data have been created. Common templates are offered by Cochrane and supplementary resources have been collected by the George Washington University Libraries. Other forms are built into systematic review manuscript development software (e.g., Covidence, RevMan), although many scholars prefer to simply use Excel to collect data.
Excel for Systematic Reviews