Once the decision has been made about which articles are to be included in the review, relevant data from each of those studies needs to be extracted. This should be done in a structured, systematic way and will usually be presented in tables in your final review report. Here are some tips:
- Only extract the data that is relevant to your research question
- Create a table or data collection form so that you can summarise the data consistently for each study
- Convert all the data to the same units of measurement, where possible
- Ensure your table headings are easily interpreted by others
- Ensure any abbreviations or acronyms used in the table are explained in the footnotes to that table
- Pilot your data extraction method before you start – especially if more than one person is extracting the data
Useful Tools
Your data can be extracted into a simple table, but if you want a more detailed approach, there are a number of analysis tools that can help. See the following:
- NVivo (CSU supported and great for qualitative data analysis)
- PSPP or JASP (Open source software)
- Elamin, M. B., Flynn, D. N., Bassler, D., Briel, M., Alonso-Coello, P., Karanicolas, P. J., . . . Kunz, R. (2009). Choice of data extraction tools for systematic reviews depends on resources and review complexity. Journal of Clinical Epidemiology, 62(5), 506-510. doi:10.1016/j.jclinepi.2008.10.016
Study Design
Sometimes it's difficult to identify the study design of a particular paper. The Centre for Evidence Based Medicine in the UK provides a useful summary of study designs and their characteristics on their website.
More Information
- Cochrane Handbook – Table 7.3a: Checklist of items to consider in data collection or data extraction