Check for Retractions
*Prior to proceeding to the data extraction stage, each study selected for inclusion should be searched individually in Retraction Watch and PubMed to identify possible retraction notices or notices of correction.* EndNote 20 and higher versions also flag retracted publications.
Data Collection
"data slide" by bionicteaching is licensed under CC BY-NC 2.0
This stage of the systematic review process involves transcribing information from each study using a structured piloted format designed to consistently and objectively capture the relevant details. Two reviewers working independently are preferred for accuracy. Data must be managed appropriately in a transparent way and available for future updates of the systematic review and for data sharing. A sampling of data collection tools are listed here.
Data Extraction Elements:
- Consider your research question components and objectives
- Consider study inclusion / exclusion criteria
- Study characteristics such as:
- Full citation
- Setting
- Duration
- Objectives
- Intervention
- Study Design and methodology
- Participant characteristics
- Outcome measures
- Results
- Study quality factors
Consult Cochrane Interactive Learning Module 4: Selecting Studies and Collecting Data for further information. *Please note you will need to register for a Cochrane account while initially on the Mayo network. You'll receive an email message containing a link to create a password and activate your account.*
References & Recommended Reading
1. Li T, Higgins JPT, Deeks JJ. Collecting data. In: Higgins J, Thomas J, Chandler J, et al, eds. Cochrane Handbook for Systematic Reviews of Interventions. version 6.2 ed. Cochrane; 2021:chap 5. https://training.cochrane.org/handbook/current/chapter-05
2. Page MJ, Moher D, Bossuyt PM, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ (Clinical research ed). 2021;372:n160. doi:https://dx.doi.org/10.1136/bmj.n160
See Item 9 – Data Collection Process and Item 10 – Data Items
3. Buchter RB, Weise A, Pieper D. Development, testing and use of data extraction forms in systematic reviews: a review of methodological guidance. BMC medical research methodology. 2020;20(1):259. doi:https://dx.doi.org/10.1186/s12874-020-01143-3
4. Mathes T, Klasen P, Pieper D. Frequency of data extraction errors and methods to increase data extraction quality: a methodological review. BMC medical research methodology. 2017;17(1):152. doi:https://dx.doi.org/10.1186/s12874-017-0431-4
5. Hartling L. Creating efficiencies in the extraction of data from randomized trials: a prospective evaluation of a machine learning and text mining tool. BMC Med Res Methodol. 2021 Aug 16;21(1):169. doi: 10.1186/s12874-021-01354-2. PMID: 34399684; PMCID: PMC8369614.