Now, what’s the best approach for catching data extraction errors?
Ideal: Have two people extract each study independently. Then compare their results and iron out any inconsistencies. If necessary, have a third person resolve any inconsistencies
Practical: Have one person extract each study, but use another reviewer to “spot check” the results, focusing on the most important data.
This is a case where the number of studies in your systematic review, your timeline, and your resources will play a role in your approach to quality control. If you have a manageable pile of studies, enough time and enough resources, you can devote two data extractors to each study.
Under a tighter deadline, or in a case where there’s an overwhelming amount of research to review, you’ll probably opt for the spot checking approach.
Congratulations! You now know how to extract data, build a form, address inconsistent data and create an approach for quality control.
It’s time to move on to the next step of conducting a systematic review: assess for risk of bias.