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Covidence: Data Extraction

Covidence is a web-based platform that streamlines the process of conducting a comprehensive literature review.

Extraction 2.0

The New Extraction 2.0 Updated September 24, 2020

Extraction 1.0 was streamlined for RCT-focused reviews. Extraction 2.0 is designed to support other study designs, other topics, or other review types.

The Covidence product team has spent the first half of 2020 creating a brand new approach to extraction. It's way more flexible, customisable, and intuitive.

Have a look here!

In the settings menu, under the option to set number of reviewers, you can choose your preferred extraction template.  The new version Extraction 2.0 is the default, or you can switch back to the original Extraction 1.0.

Watch this video produced by Covidence titled "Creating Data Extraction Forms"

How do I extract data?

Once you have completed full text screening, included articles will be moved to the "Extraction" portion of the review, where you can extract data from each study and rate its quality:

Step 1. After quality assessment, reviewers will move on to “Data Extraction”

Step 2. At “Extraction”, click “Continue”. For each study, you will see a screen like the one shown below. The center pane shows the general areas of data extraction and allows for quick navigation between each. The data extraction form has been designed to follow your PICO format. This format works best with interventional study designs, but it can be used with other study designs as well. 

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Step 3. You can add customized fields or notes in the form.  Remember to “Save” it after inputting/editing.

Note: The first study you begin data extraction for will become your "Review Template." The tables set up here will be carried over to subsequently started extractions, where they can be individually edited if needed. Only the first reviewer can edit the template; the first reviewer can be changed at any time by clicking "Manage reviewers" on the study's pane Extraction page.

Step 4. Once two reviewers have extracted data, you will need to compare their data and come to consensus. It is consensus data which will be exported later on.

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Note: If a reviewer has not collected certain data points, that will be indicated by the cell being outlined in red. Missing data will continue to appear as grey-ed out.