• Develop extraction form
• Train data extractors to use the data collection form or system
• Data extraction by 2 or more people

Pro tip: Save time and stress by piloting your data extraction form with the whole team. If there are any fields missing or unclear, it's much easier to fix them now.

In your protocol

Your protocol includes a description of how you will extract data from your screened and appraised articles.

Some elements you will need to decide about data extraction plan include:

• Who - independent duplicate extraction by 2 or more reviewers is recommended, as with the screening step
• What data will be extracted - descriptions and definitions
• Any standardized forms or checklists to be used
• Technology - some review support software has a data extraction feature, but you can also use Excel, Google Sheets, or even pencil & paper
• Method of obtaining any missing data for included articles

In your review

For a full description of the data extraction step, see Chapter 5 in the Cochrane Handbook for Systematic Reviews of Interventions or one of the other resources below:

• Chapter 5: Collecting Data (Cochrane Handbook)
• Data Extraction Training Module PowerPoint (AHRQ)
• Undertaking the Review (University of York); see section 1.3.5 Data Synthesis

What should I extract?

You should plan to extract only data that is relevant to answering the question posed in your systematic review. It may help to consult other similar systematic reviews to identify what data to collect.  You should use your key questions and your eligibility criteria as a starting point.  It can also help to think about your question in a framework such as PICO.

Data to be extracted may include:

• Information about the study (author(s), year of publication, title, DOI)
• Demographics (age, sex, ethnicity, diseases / conditions, other characteristics related to the intervention / outcome)
• Methodology (study type, participant recruitment / selection / allocation, level of evidence, study quality)
• Intervention (quantity, dosage, route of administration, format, duration, time frame, setting)
• Outcomes (quantitative and / or qualitative)

If you plan to synthesize data, you will want to collect additional information such as sample sizes, effect sizes, dependent variables, reliability measures, pre-test data, post-test data, follow-up data, and statistical tests used.

Data extraction tips

1. Examine an article that definitely belongs in the review: what data elements would you want to capture from it?
2. Look for an existing extraction form or tool to help guide you. Use existing systematic reviews on your topic to identify what information to collect if you are not sure what to do.
3. Train the review team on the extraction categories and what type of data would be expected. A manual or guide may help your team establish standards.
4. Pilot the extraction / coding form to ensure data extractors are recording similar data. Revise the extraction form if needed.
5. Discuss any discrepancies in coding throughout the process.
6. Document any changes to the process or the form. Keep track of the decisions the team makes and the reasoning behind them.