Data extraction is the process that describes the collection of relevant information about the findings and characteristics of a study that is included in a systematic review. This information is usually collected in a data extraction form which will consist of a number of elements depending on the review question. This could be done for example in a spreadsheet, or Covidence also has built in extraction tools.
Data can mean any information from a study including:
For more details see Chapter 5 of the Cochrane Handbook Section 5.3 What data to collect
Moon K, Rao S. Data Extraction from Included Studies. In: Patole S, editor. Principles and Practice of Systematic Reviews and Meta-Analysis. Cham: Springer International Publishing; 2021. p. 65-71.
Li T, Higgins JPT, Deeks JJ, editors. Collecting data. In: Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page MJ et al, editors. Cochrane handbook for systematic reviews of interventions, Cochrane; 2022.
The final part of the systematic review is to combine the results to answer the research question. This may be via a quantitative method using a statistical approach such as with a meta-analysis or it may rely on other methods of synthesis such those used in qualitative topics like meta-ethnography.
The final combination of results will be dependent on the nature of the question and the quality and homogeneity of the research.
NVivo software may be helpful for systematic reviews with qualitative data. Our Using NVivo in systematic reviews library guide has more information.
Crombie IK, Davies HT. What is meta-analysis? [Internet]. Bandolier.org.uk; 2009.
Barnett-Page E, Thomas J. Methods for the synthesis of qualitative research: a critical review. BMC Med Res Methodol. 2009;9:59.