If you have to find and organize data from hundreds (or even thousands) of studies, you’re likely to make a few mistakes along the way.
That’s why data extraction is at least a two person job. Ideally, you’d have people with different levels of expertise such as a methods expert and a subject matter expert to keep a close eye on the data. At the very least, you need another person to double check your work and make sure you didn’t miss anything. If you’re short on resources, try finding a volunteer (perhaps a student who wants to learn how to do systematic review and is willing to trade their time for your training) to help you. Or trade data extraction help with another researcher.
Once you’ve assembled a data extraction team, how do you organize their workflow to check for mistakes?
Well, there’s the ideal approach and then there’s the practical approach.