Build a customized data extraction form for your systematic review. Select from 60+ pre-built fields organized by category, reorder columns, add custom fields, and export as a CSV spreadsheet ready for your review team.
Browse the field library on the left and click fields to add them to your template. Use the arrows to reorder, add custom fields at the bottom, then export as CSV. The CSV file opens in Excel or Google Sheets with each field as a column header -- one row per study.
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Click fields in the library to add them to your extraction template.
Have two reviewers independently extract data from 3-5 studies using your template. Compare results and refine fields before starting the full extraction.
Even with structured fields, a general notes column lets reviewers flag issues, record assumptions, or note important contextual details.
Create a companion document explaining what each field means, how to handle missing data, and any coding rules. This ensures consistency across reviewers.
Organize extraction fields around Population, Intervention, Comparator, and Outcome. This maps directly to your review question and synthesis.
A data extraction form is a standardized template used in systematic reviews to collect relevant information from each included study. It typically includes fields for study identification (authors, year), population characteristics, intervention details, outcomes measured, and results. A well-designed form ensures consistent and comprehensive data collection across all reviewers.
This depends on your review scope. A focused intervention review might need 20-30 fields. A comprehensive review with subgroup analyses might need 50+. Start with your PICO elements and add fields needed for your planned analyses. Too few fields risks missing important data; too many leads to reviewer fatigue and errors.
Yes! The CSV export opens directly in Excel, Google Sheets, Numbers, or any spreadsheet application. Each field becomes a column header in your spreadsheet. You can then add data validation, dropdown lists, and conditional formatting as needed.
Yes, it's strongly recommended. Including RoB fields in your extraction form (rather than a separate document) keeps all study data in one place. Select the appropriate RoB tool for your study designs: RoB 2 for randomized trials, ROBINS-I for non-randomized studies, or NOS for observational studies.
Our team can handle the full data extraction process for your systematic review, including dual extraction, consensus resolution, and quality assurance.