In the world of systematic reviews, we often obsess over the final forest plot, treating the process that got us there as a "black box." But as any researcher who has stared down a 5,000-citation dataset knows, the validity of your conclusion doesn't rest on the software you use to generate the chart—it rests on the transparency of your decisions along the way.
As an MD and researcher, I can tell you that the complexity of modern research has outpaced the tools we use to manage it. When you are synthesizing data from dozens of heterogeneous studies, a static spreadsheet is not just inefficient; it is a liability.
This brings us to the Evidence Log.
Most platforms treat the evidence log as an afterthought—a static export you generate at the end of the project to satisfy PRISMA guidelines. But this approach is backward. A true evidence log should be the central nervous system of your review. It is the dynamic record that tracks why a specific paper was excluded in round two or how a discrepancy in outcome definitions was resolved between three different reviewers.
If your software treats your evidence log as a dusty archive rather than a living tool, you aren't just wasting time; you are risking the integrity of your entire project.
Stop wrestling with version control.
Stop losing track of critical decisions.
Start building a review that is reproducible by design.
Create Your Dynamic Evidence Log
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