An Open-Source Systematic Reviews Integrated System (OSSYRIS) - Streamlining Processes and Standardising Data...

Carrying out a systematic review (SR) of the literature entails a high workload and encompasses a variety of very different tasks. The emergence of artificial intelligence tools has brought further opportunities to improve the efficiency and reliability of SRs. SR processes can be optimised to the extent that integration and interoperability of software tools across production stages are progressively implemented. A key stage is data extraction, which can be challenging due to the large amounts of data items to consider and the variability of studies reporting styles, which heavily complicates data processing and analyses.We report the development of a software platform that integrates processes across all types of SR tasks, including overviews of SRs, is open source, and addresses the challenges of data extraction through the standardisation of data structures: the "Open-Source SYstematic Reviews Integrated System" (OSSYRIS).

We established a series of criteria to select the software integrated in OSSYRIS: few applications, covering all SRs production processes, inter-operable and open source. After several trials, we selected Zotero as reference manager, KoboToolbox XLSForms for screening and data extraction and R for analyses and reporting. We integrated all components using Application Programming Interfaces (API) in R. For the data extraction form, we identified content items from our own experience and from the Cochrane handbook. OSSYRIS has been piloted and used in several SRs and overviews carried out by the authors.

In OSSYRIS, references are manually imported in Zotero and are integrated into XLSForms in KoboToolbox, which are used for online screening by reviewers. R automatically downloads the screening results from KoboToolbox and updates the status of the references in Zotero as 'irrelevant', 'included', 'excluded,' and 'unclear'. R automatically produces the figure with the PRISMA flow of studies and references lists by status, for reporting.Data extraction is manually done using another XLSForm structured in sections: study characteristics, participants, intervention or exposure, outcomes, results and conclusion. Data extraction is standardised by using pre-coded data items, filtering data items according to relevance criteria and modularising data structures. Results of studies are entered using a data structure consistent with the information on the type of outcomes, in a form preceding section. Items that require a decision based on certain criteria, such as which is the type of study or the risk of bias assessments, are not filled in by reviewers; rather reviewers enter the criteria and OSSYRIS internal algorithms issue the specific type of study design or the risk of bias assessments, based on those criteria. XLSForms provide additional functionalities to ensure data integrity. R automatically produces the characteristics of included studies and other analytical outputs for reporting. Standardisation and modularity facilitate adapting the form for different types of SR.

OSSYRIS provides an open source, integrated system to carry out SRs. Our work may support the promotion of open source and free tools to conduct SRs bringing together a community of practice to further improve it, within Cochrane and beyond.