#HEORInsights

A well-conducted systematic review and meta-analysis can be invaluable to help clinicians stay up-to-date on current evidence-based medicine.⁽¹⁾ However, systematic reviews and meta-analyses often tend to be highly focussed on a specific research question, and as a result not broad enough to be equally useful for all stakeholders, especially in topics of broad public health importance with multiple facets involved in policy-level decision-making process. Furthermore, systematic reviews are frequently conducted by small teams of researchers, usually from a single or few institutions; while this can ensure quicker completion of the research, research resulting from a smaller team can suffer from disadvantages such as lack of diversity, limited expertise of team members, higher risk of bias, subjectivity and methodological errors, and an overall lack of generalizability.⁽²⁾

A coordinated systematic review model called the “collaborative review model” proposed by Hayden et al can address the challenges posed by the process taken up for conducting conventional systematic reviews. The collaborative review model is a relatively new approach developed for areas with significant research material on a specific health condition.⁽³⁾ This approach intends to divide a single systematic review topic into focused sub-reviews using homogeneous methods and tools and by sharing data among the team members. Collaborative input on method decisions is supported by comprehensive guidance documents shared across the network and multifaceted strategies for effective communication. Collaboration is supported by a well-defined project management structure, efficient communication strategies, and the collective harnessing of resources and skills.⁽³⁾

The collaborative review model enables team coordination and collaboration, frequent expert discussions, coordinated literature searching across a broader topic, and consistency in data handling and analytic methods. The division of large reviews into smaller, focused sub-reviews allows for increased efficiency and faster completion of reviews. By involving multiple reviewers, these reviews can minimize the risk of bias and enhance the reliability of findings. Moreover, with the use of advanced comparative and multivariable analyses, including network meta-analyses, collaborative reviews provide a comprehensive understanding of treatment effects. These analyses can offer valuable insights into treatment options and comparative effectiveness.⁽³⁾

The collaborative review approach ensures a more thorough and accurate assessment of the evidence by incorporating standardized data collection forms and consistent data handling to address discrepancies. Through task coordination and resource sharing, collaborative review approach optimizes the allocation of research resources and enhances the overall efficiency of evidence synthesis. By establishing standardized protocols, guidelines, and workflows, this approach ensures methodological consistency across review teams. Furthermore, collaborative reviews bring together the expertise of large international collaborators, promoting capacity-building and mentorship opportunities for new reviewers.⁽³⁾

This collaborative review approach is not without challenges. The involvement of a large team requires steeper funding requirements for a well-coordinated review to handle large teams, systematic review tools, and good project management. Next, given the huge number of contributors involved in such a review model, maintaining a transparent process for authorship and acknowledgment of the multiple outputs poses another significant challenge.⁽³⁾

The collaborative review model has the potential to address many barriers to getting evidence into policy by drawing on the strengths of pre-existing different approaches to evidence synthesis. The effectiveness of the collaborative review model with enhanced quality control measures provides a standardized approach to collating and summarising large volumes of evidence for policy makers for any policy topic area.

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References:

1. Tawfik GM, Dila KA, Mohamed MY, et al. A step by step guide for conducting a systematic review and meta-analysis with simulation data. Tropical medicine and health. 2019 Dec;47(1):1-9.
2. Créquit P, Trinquart L, Yavchitz A, Ravaud P. Wasted research when systematic reviews fail to provide a complete and up-to-date evidence synthesis: the example of lung cancer. BMC medicine. 2016 Dec;14(1):1-5.
3. Hayden JA, Hayden JA, Ogilvie R, et al. Commentary: collaborative systematic review may produce and share high-quality, comparative evidence more efficiently. Journal of clinical epidemiology. 2022 Sep 28.