What best defines a meta-analysis?

A meta-analysis is best defined as a statistical combination of randomized controlled trials (RCTs) to produce high-level evidence. This process involves systematically pooling data from multiple studies that address the same research question, allowing for a more robust conclusion than any single study could provide. By using statistical techniques, a meta-analysis enhances the overall power and precision of the findings, reducing the uncertainty around the effect of interventions or treatments.

This approach is particularly valuable in Evidence-Informed Practice as it provides practitioners and decision-makers with consolidated insights based on the best available evidence. The rigor of statistical methods in meta-analyses helps to minimize bias and helps identify trends and effects that may not be apparent in smaller or individual studies. The high level of evidence produced subsequently supports more informed decision-making in clinical practice.

Other options describe important components of research but do not capture the specific process and objective of a meta-analysis. For example, a detailed literature review may summarize existing studies but does not involve statistical synthesis, while a narrative summary provides a qualitative overview without the quantitative rigor that defines a meta-analysis. A synthesis of qualitative data also lacks the statistical approach that is fundamental to a meta-analysis.