- Library Research FAQ This link opens in a new window
- Systematic Review Search Strategy Tutorials
- About Data Extraction
- Determining Data to Extract
- Data Extraction Tools
- Data Extraction Tips
- Meta-analysis
- Academic Publishing 101 This link opens in a new window
- Home
- Step 0: Pre-Review Tasks
- Step 1: Systematic Review Protocol Development
- Step 2: Choose Systematic Review Tools
- Step 3: Develop a Systematic Review Search Strategy
- Library Research FAQ This link opens in a new window
- Systematic Review Search Strategy Tutorials
- About Data Extraction
- Determining Data to Extract
- Data Extraction Tools
- Data Extraction Tips
- Meta-analysis
- Academic Publishing 101 This link opens in a new window
About Data Extraction
The purpose of the data extraction process is to provide evidence which answers your PICO question.
Data is summarized in tables which will provide a high-level overview of the findings.
Evidence and summary table will describe study characteristics, results or both.
Data extraction tools are detailed below.
The Cochrane and JBI guidelines strongly suggest at minimum of 2 reviewers extract and summarize data to reduce errors and bias.
Determining Data to Extract
Examples of data extracted for an intervention question:
- Author(s), year of publication, title, DOI
- Study type, participant recruitment/selection/allocation, level of evidence, study quality
- sample sizes, effect size, dependent variables, reliability measures, pre and post-test data and statistical tests applied
For additional data extraction criteria refer to:
and remember to review similar systematic reviews for examples of data extraction
Data Extraction Tools
Covidence: allows you to create and publish a data extraction template with text fields, single choice items, section headings and subheadings, perform dual reviewer data extraction, review extractions for consensus and export data extracted to a csv file.
- How to get started with data extraction
- Turn your protocol into a data extraction framework
- How to create and publish a data extraction template
- How to extract data and assess quality
- How to do comparison and consensus
- How to export extracted data to Excel using Data Extraction 2.0
Spreadsheets or Database Software (Excel or Google Sheets):
Spreadsheets or database software can be used to create custom extraction forms. Spreadsheet software (such as Microsoft Excel) has functions such as drop-down menus and range checks which can perform data collection efficiently and help to prevent data entry errors.
Review Manager (RevMan) is Cochrane's software for preparing and maintaining Cochrane reviews. RevMan facilitates preparation of protocols and full reviews, including text, characteristics of studies, comparison tables, and study data. It can perform meta-analysis of the data entered, and present results graphically.
Survey or Form Software (Qualtrics, Poll Everywhere or Google Forms)
These tools allow the reviewers to create custom forms with a variety of question types to collect data in a standardized format
- Qualtrics can be found in the ATSU portal
Data Extraction Tips
For a smooth data extraction process with less risk of bias:
- Use existing systematic reviews on your topic to identify what information to collect if you are not sure what to do.
- 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.
- Pilot the extraction / coding form to ensure data extractors are recording similar data. Revise the extraction form if needed.
- Discuss any discrepancies in coding throughout the process.
- Document any changes to the process or the form. Keep track of the decisions the team makes and the reasoning behind them.
