The Data Extraction stage in Rayyan helps you collect structured information from the studies selected for your review. Instead of working with unstructured notes, you can create custom extraction fields, organize them into sections, and standardize how reviewers capture data across articles.
This is especially useful when you need to extract study characteristics, outcomes, sample details, or any other variables required for analysis and synthesis.
Steps to Extract Data in Rayyan
1. Access the Data Extraction Stage
From your Review Dashboard, open the Data Extraction tab.
This stage is designed for extracting structured information from articles that have already passed the screening stages.
2. Add Articles
You can add articles from either:
- The Screening Stage, or
- The Full-Text Screening (FTS) Stage.
Select from:
- Included list
- Maybe list
- Any Labelled articles
This flexibility allows you to extract data only from relevant records.
3. Upload PDFs
If full-text PDFs were not uploaded earlier, you can upload them now.
Having PDFs available during extraction helps reviewers verify information and answer extraction questions accurately.
4. Create Your Custom Questions
Click the ➕ Add Question icon on the right-hand side to add questions.
5. Enter a column title
In Column Title, add the name that will appear in the extraction table.
This should be short and descriptive, since it becomes the column header reviewers will see while extracting data.
Examples:
Study design
Sample size
Intervention
-
Outcome measure
6. Write the extraction question
In the Question field, enter the prompt reviewers should answer for each article.
This field should clearly describe what information needs to be extracted from the study.
For example:
What is the study design?
How many participants were included?
What intervention was evaluated?
Using clear wording helps reduce inconsistencies across reviewers.
7. Select the answer type
Rayyan lets you define the expected response format for each question. The available answer types are:
Free Text — for open-ended answers
Numbers — for numeric values
Specified — for predefined response options
Choosing the correct answer type helps standardize responses and improves the quality of your extracted dataset.
8. Mark a question as required when needed
You can enable the Required Question toggle if a field must be completed.
This is useful for key variables that should never be left blank, such as primary outcome, sample size, or study type.
9. Organize questions under a group or section
Rayyan also allows you to place questions under a group.
In the setup panel, use Group under to either:
assign the question to an existing section, or
create a new group
Don´t forget to save changes!
This helps organize your extraction form into logical sections, especially when you have many variables.
For example, you might create groups such as:
Study Characteristics
Population
Intervention
Outcomes
10. Click Add Question to save it
Once the fields are complete, click Add Question.
The new question will then appear as a column in the extraction table.
11. Organize Your Extraction Columns
You can drag and drop columns to reorder them in the extraction table.
This makes it easier to:
group related variables
align extraction fields with your protocol
improve readability during data collection.
12. Start Extracting Data
Once questions are defined, click Extract Data in the toolbar.
Extraction questions will appear in dropdown sections, allowing you to focus on specific groups of variables while reviewing an article.
During extraction you can use the built-in PDF viewer to:
Zoom in or out
Rotate pages
Scroll through the document
Use side-by-side view for easier comparison
13. Manage Extraction Progress
While extracting data for each article you can choose.
Delete — when you want to delete the question.
Save changes — if you need to pause and return to complete it later.
These options help you manage progress flexibly, especially when working across large sets of articles or collaborating with a team.
14. Track Progress with Filters
You can filter the extraction table by progress status:
• All Data
• Not Started
• Uncompleted
• Completed
This helps review owners monitor progress and assign workloads across reviewers.
15. Blinding and Conflict Resolution
When multiple reviewers are working on data extraction, blinding is important to reduce bias and ensure independent work.
Here’s how it works in Rayyan:
While blinding is on, each reviewer completes data extraction independently — they can only see and edit their own answers.
The review owner can turn off blinding at any point to review team progress.
Once blinding is turned off you can:
✅ Resolve disagreements — to align the data, each reviewer needs to adjust their answers where mismatches are found, ensuring consistent and agreed-upon extraction results.
✅ Export the final data — once all conflicts are resolved and answers aligned, you can export the clean dataset.
This workflow ensures that your extracted data is both independent at first and harmonized before export — a critical step for maintaining rigor in systematic reviews.
Once answers are aligned, the dataset is ready for export.
16. Export Your Extraction Data
You can export the extracted data as a CSV file.
Exports can include:
All articles
Filtered results only
The download link will be sent to your email and also posted in Review Chat.
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