Anticipate what the data summary table will need to include. Use the PICOTframework to choose data elements in the data extraction form. Reviewers should develop the standardised form to suit the specific Systematic Review 1 and use the key question(s) and inclusion and exclusion criteria as a guide. Using the excel spreadsheet allows for more customisation of what data to collect. If the Systematic Review includes a meta-analysis and/or reviews a large number of studies the data extraction software will likely be helpful.

Tools available for data extraction include an Excel spreadsheet or the data extraction templates in software like Covidence. Ideally, at least two reviewers should work independently, to extract quantitative and other critical data from each study, and a fair procedure for resolving discrepancies should be established. If the Systematic Review is a narrative (no meta-analysis) and/or reviews a relatively small number of studies, coding is probably unnecessary. The standardised data extraction form is as long or as short as necessary and can be coded if desired, especially if a quantitative analysis is required.

Obtain information to objectively assess the risk of bias in, and applicability of, studies.

Identify numerical data if a meta-analysis is to take place, and.

Objectively and accurately summarize studies in a common format to facilitate synthesis,.

The purpose of the data extraction step is to: Once the search and selection of studies for inclusion is completed the next step is to read the full text of each article identified for inclusion in the Systematic Review and extract the relevant data using a standardised data extraction form.

Data extract software