The data extraction step in a standard systematic review is similar to the screening process. Each study is typically extracted by two team members to prevent mistakes or bias and if needed, a third reviewer resolves disagreements. Extractors also put data into a standardized form to ensure that their information is organized and in the same format. It takes time to design these forms, go through every study twice, and, where necessary, contact study authors about missing or inconsistent data.
Here are some typical ways to modify and speed up the extraction process:
- Extract less! A narrow question leads to a more focused and quicker review. Narrow down the scope of your review or the depth of your question so you’re gathering less data from each study
- Use a single extractor for each study (if possible try to have a second extractor verify at least a portion of the outcome data)
- Prioritize certain studies. For example, only extract from recent studies that are most relevant to your review or have the most rigorous study design. However, if doing this – remember to at least provide a list of the other included studies that were not extracted
- When extracting, do not extract full outcome data (results including effect estimates) until your data analysis plan is finalized, which usually happens once all included studies are selected. Don’t waste time pulling out information you won’t use.
Consequences of this shortcut
Systematic data extraction forms allow reviewers to apply the same lens to all studies and ensure all relevant data is captured, objectively. By not using a standardized form, reviewers may forget to include important details.