VU Systematic Literature Reviews: Extraction

Data extraction overview

The findings of a systematic review will be based on the data extracted from the included studies. "Data collected for systematic reviews should be accurate, complete, and accessible for future updates of the review and data sharing" (Cochrane handbook, Ch. 5).

The module above from the University of South Australia describes the steps in the data extraction process. A video from Dr Saravana Kumar provides important tips for reviewers on preparing a data extraction worksheet. 

The resources  on this page provide tips on data extraction and links to guidelines and standards relating to the data extraction stage of a systematic review. 


Data extraction forms

Data collection for systematic reviews should be performed using structured data collection forms (Li et al., 2022, 5.4.1). Data collection forms can be paper-based or electronic, or from commercially available products, such as Covidence. Each systematic review will have a customized data extraction form (or forms), specifically designed to extract  the data required to answer the review question. It is important that review teams  pilot the data extraction form to test its usability (Li et al., 2022,  5.4.1).


  • It is highly recommended that two independent reviewers extract data from included studies, to reduce bias and ensure quality control
  •  Use one data-extraction worksheet for an individual study, so that one data-extraction worksheet will contain the information gained from several publications on the same study. 
  • If several different studies are mentioned in one publication, the data of each should be extracted in a separate data extraction worksheet.
  • Fill in every field as it must be obvious from the form if certain information is missing 
  • Pilot the data extraction form with a small number of studies and all reviewers. This will ensure all reviewers have an understanding of the data expected for each category. The form may need revisions after the pilot.

Fields commonly included in data extraction forms include those listed below. Remember data extraction forms need to be customized for individual systematic reviews. 

  • article citation
  • study methods, including study design, recruitment and sampling procedures
  • participant characteristics
  • intervention or exposure
  • outcome data and results

Further resources

The articles below provide guidance on data extraction for meta-analyses:

Covidence data extraction (webinar)

This webinar from Covidence 101 training provides an overview of the Data Extraction 2.0 feature in Covidence, tips on how to develop a data extraction template and tips on the extraction process in Covidence.