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Structured data extraction for systematic reviews

Pull the same fields — sample size, design, outcomes, effect sizes — out of every included study into one clean, exportable table.

F

Folio Team

May 14, 2026 2 min read

On this page

  • The idea
  • Why it matters
  • Where we are

The idea

A step beyond the synthesis matrix: define the exact fields your review needs — sample size, study design, population, intervention, outcome measures, effect sizes, risk-of-bias rating — and extract them from every included paper into a single structured table. Folio drafts each cell from the source; you verify and correct; the whole thing exports to CSV or straight into your meta-analysis.

Why it matters

Data extraction is the most tedious, error-prone stage of a systematic review, and it's usually done by hand across a dozen spreadsheets with two reviewers reconciling differences. A structured, source-linked extraction table — where every number is traceable to the sentence it came from — cuts the drudgery and makes the reconciliation honest. It's the difference between a review that takes a semester and one that takes a month.

Where we are

Exploring, and a strong fit with the synthesis matrix that already exists. The bar is traceability: every extracted value has to point back to its exact place in the source, or it's not trustworthy enough to build a meta-analysis on. That's the part we want to get right before shipping.

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