Data Extraction and Evidence Synthesis
Data extraction pulls a consistent, verifiable dataset out of every included study; evidence synthesis turns that dataset into a defensible answer to the research question. EviMeRx delivers both with documented quality control.
Once the included set is locked, the review has a body of studies but not yet an answer. Extraction converts heterogeneous publications into a single structured dataset, and synthesis interprets that dataset — qualitatively, quantitatively, or both — into conclusions that hold up under review.
What data extraction covers
Extraction captures, per included study:
- Study characteristics — design, setting, country, funding, follow-up duration
- Population — sample size, demographics, disease severity, inclusion criteria
- Interventions and comparators — dose, route, schedule, duration
- Outcomes — efficacy, safety, quality of life, health economic endpoints
- Results — effect estimates with measures of variance, and the analysis population they derive from
Standardised extraction templates
The template is built from the protocol and piloted on a small number of studies before full extraction. Piloting catches the fields that turn out to be ambiguous or unavailable across the literature — far better found at study three than at study sixty, when every earlier form would need revisiting.
Verification and traceability
Extracted data is independently verified against the source publication, so every value in the final dataset can be traced back to a specific table, figure or paragraph. Traceability is what allows a reviewer, a regulator or a journal to check any number in your submission against its source — and it is the first thing an HTA assessor tests.
Quality and risk of bias assessment
Included studies are appraised using the instrument appropriate to their design, with the choice specified in the protocol. The assessment is what allows the synthesis to weight the evidence rather than treat every study as equally reliable, and it is reported per study and per domain so readers can see how the judgement was reached.
Qualitative synthesis
Where studies are too heterogeneous to pool — different populations, comparators, outcome definitions or timepoints — the synthesis is narrative. Done properly this is not a summary of each paper in turn: it groups studies by the question they inform, states what the evidence supports, and is explicit about where it conflicts or runs out.
Quantitative synthesis and meta-analysis
Where studies are sufficiently comparable, effect estimates are pooled. This includes assessing clinical and statistical heterogeneity, selecting fixed or random effects on stated grounds, running the planned subgroup and sensitivity analyses, and testing for small-study effects. Every decision follows the protocol rather than the results.
What you receive
The verified extraction dataset; evidence tables formatted for publication or submission; the quality and risk-of-bias assessment per study; the narrative synthesis; and, where applicable, the meta-analysis with forest plots and the full analysis log.