This will allow the team to see the data from each individual research study in a comparative fashion, and at the same time. Identify the data you wish to extract - your data extraction will likely replicate aspects of your research formula, e.g. for a PICO question (Population, Intervention, Comparison, Outcomes). Build and test your data extraction form and/or data tables – Google Form could be a useful tool here, or build tables in Word, Excel. If you are using a systematic review software, you may wish to see what tools exist within the product.
For more information on the data extraction process, see Ch. 6 in Doing a Systematic Review: A Student's Guide.
Some examples of different approaches to data extraction and display are viewable in the below articles:
• Narrative approach (see table S3): Poulsen, M. N., McNab, P. R., Clayton, M. L., & Neff, R. A. (2015). A systematic review of urban agriculture and food security impacts in low-income countries. Food Policy, 55, 131-146. doi:10.1016/j.foodpol.2015.07.002
• Numerical approach (see tables 1 and 2):
Azad, M. B., Abou-Setta, A. M., Chauhan, B. F., Rabbani, R., Lys, J., Copstein, L., Zarychanski, R. (2017). Nonnutritive sweeteners and cardiometabolic health: A systematic review and meta-analysis of randomized controlled trials and prospective cohort studies. CMAJ: Canadian Medical Association Journal, 189(28), E929. doi:10.1503/cmaj.161390