|Let's develop study-centric data in RevMan Web together!
Contact us here to impact development by joining demos and giving feedback during implementation
What is study-centric data?
Using study-centric data in RevMan Web means that extracted result data is added in the included studies, rather than in the Analysis. Authors will define the PICO for their analysis, and RevMan Web will automatically identify the eligible studies and data and create your analysis. The old way of entering result data in the analysis data table will still be available as an option.
Why is it important?
The main motivations to move to study-centric data are to support smooth integration with tools such as Covidence and the introduction of Network Meta-Analysis and other new methods in RevMan Web. There are also immediate benefits for Cochrane authors and editors:
- Reduces duplication of data and thereby the risk of introducing errors
- Clear workflow for authors in reviews
- Facilitates updates of reviews as forest plots will be updated automatically when new studies are included
- Provenance of result data is improved as data that is entered in the calculator will be saved
When is it coming?
The first iteration of study-centric data is now implemented by the Review Production Team in CET, IT Services. You can explore a review with study-centric data in a Practice review. Guidance with how-to articles and video tutorials on how to use study-centric data and how it’s different can be found in the Knowledge base. To join the pilot, contact email@example.com.
Training and support for trainers, editors and authors is planned to ensure a smooth introduction. Moving to study-centric data will be a decision made by the review groups on a review-by-review basis.
How will it work?
When study-centric data is enabled for a review you will be able to define review level PICOs: Study characteristics (P), Interventions (IC), Outcomes (O).
When extracting data for an included study you will be able to enter not only study characteristics and risk of bias but also the reported result data. To do this, you will first define the arms of the study and assign interventions to them. Following this you will be able to enter result data for each relevant outcome.
After entering result data within the included studies, you will be able to create analyses by choosing the outcome and the control and experimental interventions. This will automatically detect and include the studies that fulfill the criteria and generate a forest plot. RevMan Web will automatically combine arms as necessary. You will be able to use study characteristics to create subgroups within the analysis, or to exclude studies from the analysis completely.