Research Guides: Systematic Reviews: How-To: 7. Extract the Data

7. Extract the Data

Data Extraction

Just as with the risk of bias assessment, data extraction should be conducted by two blinded, independent, reviewers to reduce bias and ensure data quality control.

Developing a form

A data extraction form should be developed early in the review planning process using the research question and inclusion criteria to customize the form to meet the needs of the project.

Commonly extracted fields for most SRs include:

article citation with corresponding author
study characteristics such as study type
participant characteristics
interventions and setting
outcome data & results

To help develop the data extraction form, teams can use existing systematic reviews on their topic to identify what potential information to collect. If the team is planning to do a statistical analysis or meta-analysis they should consult with a biostatistician for advice on what numerical data should be collected.

Manuals, such as the Cochrane Handbook, provide starting templates for data extraction.

Cochrane Data Extraction Template
This form can be used as a guide for developing your own data extraction form. Sections can be expanded and added, and irrelevant sections can be removed.
Example Data Extraction Form for Systematic Reviews This example is taken from the appendix of Wilson, P.M., Farley, K., Bickerdike, L., Booth, A., Chambers, D., Thompson, C., Lambert, M., Turner, R., & Watt, I. (2017). Effects of a demand-led evidence briefing service on the uptake and use of research evidence by commissioners of health services: a controlled before-and-after study. NIHR Journals Library (Health Services and Delivery Research, No. 5.5.) Appendix 2, Example data extraction form for systematic reviews. Available from: https://www.ncbi.nlm.nih.gov/books/NBK424005/
JBI Template Found in the JBI Manual Appendix 11.1 JBI template source of evidence details, characteristics and results extraction instrument.
Cochrane Chapter 5: Collecting Data
National Academies Press/IOM Manual: Managing Data Collection

Software specifically build for doing systematic reviews often have data extraction forms built in to them that can be adjusted to fit the team study and then can additionally assist in the comparison and arbitration in the event of different answers.

Pilot the form and train your team

The review team should be trained on the data extraction form and what type of data would be expected for each category. Refer to the systematic review manuals to help your team establish standards. Then the team should pilot the extraction form using 5 to 10 randomly selected studies to ensure data extractors are recording similar data. Revise the extraction form if needed. To help with writing the manuscript and maintaining transparency in the process, document any changes to the process or the form and keep track of the decisions the team makes and the reasoning behind them.