Systematic Reviews

Role of the librarian in this stage

A librarian can advise you on data extraction for your systematic review, including: 

  • What the data extraction stage of the review entails
  • How to choose what data to extract from your included articles 
  • Finding examples in the literature of similar reviews and their completed data tables
  • Best practices for reporting your included studies and their important data in your review

 

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About data extraction

In this step of the systematic review, you will develop your evidence tables, which give detailed information for each study (perhaps using a PICO framework as a guide), and summary tables, which give a high-level overview of the findings of your review. You can create evidence and summary tables to describe study characteristics, results, or both. These tables will help you determine which studies, if any, are eligible for quantitative synthesis.

Data extraction requires a lot of planning.  We will review some of the tools you can use for data extraction, the types of information you will want to extract, and the options available in the systematic review software used here at UNC, Covidence.

How many people should extract data?

The Cochrane Handbook and other studies strongly suggest at least two reviewers and extractors to reduce the number of errors.

Data extraction tips

  1. Look for an existing extraction form or tool to help guide you.  Use existing systematic reviews on your topic to identify what information to collect if you are not sure what to do.
  2. Train the review team on the extraction categories and what type of data would be expected.  A manual or guide may help your team establish standards.
  3. Pilot the extraction / coding form to ensure data extractors are recording similar data. Revise the extraction form if needed.
  4. Discuss any discrepancies in coding throughout the process.
  5. Document any changes to the process or the form.  Keep track of the decisions the team makes and the reasoning behind them.

Tools for data extraction

Covidence Logo

Systematic Review Software

Most systematic review software tools have data extraction functionality that can save you time and effort.  Here at UNC, we use a systematic review software called Covidence. You can see a more complete list of options in the Systematic Review Toolbox.

Covidence allows you to

Covidence's new data extraction features are detailed in the "Data Extraction in Covidence"  box at the end of this page.


Excel logo

Spreadsheet or Database Software

You can also use spreadsheet or database software to create custom extraction forms. Spreadsheet functions such as drop-down menus and range checks can speed up the process and help prevent data entry errors. Relational databases (such as Microsoft Access) can help you extract information from different categories like citation details, demographics, participant selection, intervention, outcomes, etc.


RevMan logo

RevMan

RevMan offers collection forms for descriptive information on population, interventions, and outcomes, and quality assessments, as well as for data for analysis and forest plots. The form elements may not be changed, and data must be entered manually.  RevMan is a free software download.


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Form or Survey Software

Survey or form tools can help you create custom forms with many different question types, such as multiple choice, drop downs, ranking, and more.  Content from these tools can often be exported to spreadsheet or database software as well.  Here at UNC we have access to the survey/form software Qualtrics.


Electronic Documents or Paper & Pencil

In the past, people often used paper and pencil to record the data they extracted from articles. Handwritten extraction is less popular now due to widespread electronic tools.  You can record extracted data in electronic tables or forms created in Microsoft Word or other word processing programs, but this process may take longer than many of our previously listed methods.  If chosen, the electronic document or paper-and-pencil extraction methods should only be used for small reviews, as larger sets of articles may become unwieldy. These methods may also be more prone to errors in data entry than some of the more automated methods.

What should I extract?

You should plan to extract data that is relevant to answering the question posed in your systematic review.  As mentioned previously, it may help to consult other similar systematic reviews to identify what data to collect.  You should use your key questions and your eligibility criteria as a starting point.  It can also help to think about your question in a framework such as PICO.

Helpful data may include:

  • Information about the study (author(s), year of publication, title, DOI)
  • Demographics (age, sex, ethnicity, diseases / conditions, other characteristics related to the intervention / outcome)
  • Methodology (study type, participant recruitment / selection / allocation, level of evidence, study quality)
  • Intervention (quantity, dosage, route of administration, format, duration, time frame, setting)
  • Outcomes (quantitative and / or qualitative)

If you plan to synthesize data, you will want to collect additional information such as sample sizes, effect sizes, dependent variables, reliability measures, pre-test data, post-test data, follow-up data, and statistical tests used.

Data extraction in Covidence

Extraction 2.0

Covidence has updated their extraction features!  You can use the editor to add fields to your extraction templates, or you can create your own from scratch.

Accessing your data extraction template

To access extraction, from the Review Summary screen, select the number of studies you have to extract. 

To access your template, select Data Extraction Template, located above the included study list. 

The data extraction template has three panels: the editor in the center, the preview on the right, and any item settings or notes to extractors on the left.

 

 

 

 

 

 

 

 

 

 

 

 

The Editor is in the center. You can fully edit the template in the Editor

The Preview is on your right. It’s a preview of what the extraction form will look like. When you change something in the Editor, the change will be reflected in the Preview. 

The Item settings are on your left. Select an item in the Editor to change its settings, such as instructions to extractors.

Add an item 

To add an item, select the Add (+) button above where you want to add the item and choose one of the following options: 

  • Text field. Use this to extract text and numbers. When extracting, the size of the text field will increase to accommodate the amount of text that’s being entered. 
  • Single choice item. Use this when you have a defined list of options and you want the extractor to choose one. 
  • Heading or Subheading. Use these to group and separate your items.

Instructions to extractors 

Text fields and single choice items allow you to communicate item specific instructions to your extractors. For example, for a single choice item, you might want to communicate to your extractors that they should only select an option if specific criteria are met. To add instructions, select the item, and then add the text in Item settings. The text will appear in the extraction form under the item’s label.

Save and Publish 

You’ll need to press Save in the upper right corner to retain any changes you’ve made to your template. If your template isn’t published yet, press Publish and reviewers will be able to start extracting their first study. To start extraction, you must publish a data extraction template, however quality assessment is optional. 

Note: If you start extracting a study, you will not be able to change the form for that study. If you're unsure about whether you'll need to make changes, pilot your form outside of Covidence first. 

To find more information on this method of extracting data in Covidence, check out the Covidence Knowledge Base

Data Extraction (original)

When you begin data extraction, 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.

Note that 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. 

The first study you begin data extraction for in each review 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.

Data extraction template including categories for Summary, Identification, Methods, Population, Interventions, Outcomes.

To find more information on extracting data in Covidence, check out the Covidence Knowledge Base

For general data extraction principles and instructions, check out the resources in the Data Extraction Guides box.