After completing the tagging hierarchy within your project, you have the option to initiate Smart MA Extraction (SMAE)—a powerful feature designed to facilitate rapid-scope meta-analysis with minimal manual effort.
Leveraging Quantitative Synthesis, SMAE automatically extracts and harmonizes quantitative data from the tagged evidence. This structured data is then seamlessly integrated into pooled estimate models and Network Meta-Analyses (NMAs), enabling faster and more consistent generation of evidence-based insights.
Smart MA Extraction is especially useful for users seeking to quickly validate a research hypothesis or perform an exploratory meta-analysis without engaging in time-consuming manual data extraction.
To begin a Smart MA Extraction, click the MA Extraction button located in the bottom corner of the Tagging screen. This will open the tagging hierarchy for your project. Within this view, a gold “Extract” button appears in the upper left corner—clicking this will initiate the Smart MA Extraction process.
You will be prompted to enter your research question, which helps guide the automated extraction. Once submitted, Nested Knowledge will process the data using its Quantitative Synthesis engine. Within a few minutes, the system will automatically extract and harmonize relevant data, displaying an expanded tagging hierarchy. This enriched hierarchy is ready for immediate use in pooled estimate models or Network Meta-Analyses (NMAs).
Once Smart MA Extraction is complete, the extracted data will be available within the MA Extraction field. This view enables users to identify the interventions that were automatically extracted and included in the analysis. Each data point is clearly linked to its source, with direct references to the original tables, allowing for easy traceability and verification.
The extracted data elements are also accessible within the Quantitative Synthesis module. Throughout each phase of synthesis, these data points remain available for review and further analysis. Within the NMA interface, users can drill down into specific interventions of interest, enabling a more detailed and customizable exploration of the synthesized data.
This streamlined process significantly expands the possibilities for data extraction, offering users a powerful yet accessible way to generate high-quality analytic outputs. With just a few clicks, users can initiate extraction and selectively toggle which data elements to include or exclude—making advanced synthesis both efficient and user-friendly.
Here is a video that explains the process:
