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The advancement of evidence-based medicine (EBM) depends on the evidence hierarchy, a framework for classifying research approaches according to their dependability and quality. It dates back to the middle of the 20th century and classifies techniques such as expert opinions, case reports, randomized controlled trials, and systematic reviews. However, problems such as prejudice and moral constraints still exist. Evidence paradigms are being redefined by emerging technologies such as artificial intelligence, big data, and real-world data. This calls for dynamic hierarchies that include many forms of evidence. High-quality data are essential for developing flexible frameworks for contemporary medicine and influencing clinical guidelines, public health regulations, and educational initiatives.
Vatkar et al. (Wed,) studied this question.