Study protocol for evaluating automation of systematic review processes with EPPI-Reviewer and Copilot 365 in updating the cataract evidence gap map

To assess the accuracy and efficiency of Copilot 365 and prioritisation screening integrated into EPPI-Reviewer at different stages of an evidence gap map update, comparing it to human performance.

The process of developing and updating an evidence gap map (EGM) is based on the principles of systematic reviews and requires extensive time and financial resources. Artificial intelligence (AI) tools, like prioritisation screening (PS), integrated into programmes such as EPPI-Reviewer (ER) and Copilot 365, integrated into programming can potentially mimic human performance in systematic review processes. The study will conduct both manual and automated screening of references, full-text screening, data extraction and critical appraisal.

This study will offer insights into ER’s accuracy in screening small samples of citations and potentially guide future applications in this context. Additionally, by evaluating Copilot 365, which shares similar features with other AI tools, we will gain a broader understanding of its applicability and limitations in evidence synthesis, making the results relevant to other AI applications in this field.