This chapter provides a practical, methods-first roadmap for designing, conducting, and reporting narrative and systematic reviews in surgery. It explains how disciplined question formulation using PICO anchors eligibility, outcomes, and analysis; how to build reproducible, librarian-reviewed searches; and how to perform calibrated dual screening with clear reasons for exclusion. It then operationalizes data extraction for surgical interventions, explicitly capturing operator expertise, center volume, learning curves, device generations, and perioperative pathways. The chapter presents a conservative approach to synthesis: domain-based risk-of-bias judgments aligned to design, random-effects models with appropriate estimation and inference, and explicit use of prediction intervals. It describes when to escalate to network meta-analysis and how to evaluate transitivity and consistency, and it closes with reporting that meets PRISMA-family expectations and with GRADE-based translation of relative effects into absolute differences that matter to patients and systems.