Stage 4: Extracting Data: Step 1: How to Plan for Data Extraction

Planning for Data Extraction

Data extraction is the process of extracting the relevant data from included studies using a standardized data extraction form. Before you do that, however, you must identify what data you are interested in extracting and plan how you are going to organize that information.

Your goal by the end of this step is to have developed a valid and comprehensive data extraction form.

“Given the important functions of data collection forms, ample time and thought should be invested in their design” Cochrane Handbook, Section 7.5.1

Identify what Data needs to be Extracted

The type of information that you extract will be based your research question. According to the Cochrane Handbook (Section 7.3.1), data is defined as “any information about (or deriving from) a study, including details of methods, participants, setting, context, interventions, outcomes, results, publications and investigators”.

When identifying what information you are going to extract, think about what might be pertinent to addressing your research question.

The following are a brief sample of data extraction forms that may be adapted for your review (provided by the University of Ottawa):

• Data extraction form example (suitable for small-scale literature review of a few dozen studies)
• Data extraction form example from Dalhousie University (uncoded & used to extract fine-detail/many variables)

For assistance in developing categories for your data extraction form, you may refer to the following resources:

• Existing data extraction forms (see Additional Resources at bottom of page for examples)
• Checklists and Review Group guidelines: For example, Cochrane Reviews and JBI have a number of required categories (see Additional Resources for this information).

Choose a Data Extraction Tool

Once you have identified the categories that you will include in your data extraction form, you can choose the tool you will use to create your form. This can vary from:

What you choose will depend on the type of data you are extracting, the complexity of your review, and your personal preferences.

For more information on the advantages and limitations of each extraction tool, refer to Elamin et al. (2009) in Additional Resources at the bottom of this page.

Pre-test Data Extraction Form

It is wise to pre-test your data extraction form to ensure that you have:

1. Identified all of the information required for your topic
2. Addressed and resolved any confusions regarding coding and coding categories

When you have finalized your data extraction form:

Although not required, it is a good idea to have multiple people involved with data extraction to decrease bias. Further, the location of data in articles is not consistently placed which may result in missed or misinterpreted information.

Additional Resources

• Li T, Higgins JPT, Deeks JJ (editors). Chapter 5: Collecting data. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.2 (updated February 2021). Cochrane, 2021.
• Choice of data extraction tools for systematic reviews depends on resources and review complexity: Elamin, M. B. et al. (2009). Journal of clinical epidemiology, 62(5), 506-510.

Data extraction forms that may be able to be adapted to your review (provided by the University of Ottawa):

• Data extraction form example (suitable for small-scale literature review of a few dozen studies)
• Data extraction form example Dalhousie University Library Guide (uncoded & used to extract fine-detail/many variables)