Data extraction is the process of extracting the relevant pieces of information from the studies you are including in your review. This also includes organizing the information in a way that will help you synthesize the studies and draw conclusions.
For both quantitative and qualitative syntheses, the data extraction will often become "Table 1" of the published manuscript, or "Characteristics of included studies." For quantitative synthesis, this is where team will collect the necessary data to carry out meta-analysis.
The data points that will be extracted from each study should be predefined in the protocol.
Li T, Higgins JPT, Deeks JJ (editors). Chapter 5: Collecting data. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.
Much like the study selection process, data extraction should be performed in duplicate. Having more than one person extracting data from every included report helps to minimize errors and reduce bias introduced by the review authors.
Data collection for systematic reviews should be performed using structured data collection forms. These can be paper forms, electronic forms (Google Form, Excel, REDCap), or commercially or custom-built data systems (Covidence, EPPI-Reviewer, Systematic Review Data Repository (SRDR)) that allow online form building, data entry by several users, data sharing, and efficient data management. All different means of data collection require data collection forms.
Review authors often have different backgrounds and level of systematic review experience. Using a data collection form ensures some consistency in the process of data extraction, and is necessary for comparing data extracted in duplicate. Piloting the form within the review team is recommended.
Covidence has produced a helpful guide on the data extraction process, available for free download, here: https://www.covidence.org/resource/data-extraction-for-intervention-systematic-reviews/
Li T, Higgins JPT, Deeks JJ (editors). Chapter 5: Collecting data. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.
The type of data extracted will depend on the clinical question informing the review. However, extracted data will often include both study characteristics and outcome data.
Items to consider in data collection
Not all of the following points will be relevant for all reviews.
Information about data extraction from reports
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Study methods
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Participants
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Intervention
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Outcomes
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Results
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Miscellaneous
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(Table 5.3.a in Li T, Higgins JPT, Deeks JJ (editors). Chapter 5: Collecting data. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.)