Evidence-based medicine: is it a bridge too far?

Area of Science:

• Philosophy of Science
• Complexity Science
• Health Systems Research

Background:

• Evidence-based medicine (EBM) emerged due to standardization needs, clinical epidemiology growth, economic concerns, and increased clinical trials.
• EBM's rapid adoption was based on authoritative knowledge rather than proven system improvements.
• The rise of computing power facilitated handling large datasets, contributing to EBM's development.

Purpose of the Study:

• To describe the contextual factors leading to evidence-based medicine (EBM).
• To analyze the controversies and limitations of EBM in the current health context.
• To apply complex adaptive systems and philosophy of science frameworks to understand EBM.

Main Methods:

• Utilized a complex adaptive systems view of health and healthcare.
• Employed a unified approach to the philosophy of science.
• Analyzed the phases of scientific discovery, corroboration, and implementation.

Main Results:

• EBM prioritizes internal validity and explanatory randomized controlled trials, which are insufficient for implementation.
• The current EBM approach offers a restricted view of scientific knowledge.
• Explanatory randomized controlled trials are useful for discovery but inadequate for implementation, which requires additional data like expert knowledge and patient values.

Conclusions:

• Evidence-based medicine (EBM) must evolve to recognize health and healthcare as complex, interconnected, non-linear phenomena.
• Complexity science techniques offer a better analytical approach for understanding health and healthcare.
• A more integrated approach is needed to address EBM's limitations in real-world healthcare settings.