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Toward Complex-Systems Evidence for Chinese Medicine: A Four-Phase Evidence Framework.

Xuxu Wei1,2, Xinyu Yang3, Xiaoyu Zhang4

  • 1Beijing University of Chinese Medicine, Beijing, China.

Journal of Evidence-Based Medicine
|March 11, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a complex-systems evidence framework for Traditional Chinese Medicine (TCM). It bridges the gap between evidence generation and clinical application by integrating qualitative and quantitative methods for better decision-making and research.

Keywords:
evidence‐based medicineopen complex giant system (OCGS)personalized medicinetraditional Chinese medicine (TCM)translational medicine

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Area of Science:

  • Systems Science
  • Artificial Intelligence
  • Traditional Chinese Medicine (TCM) Research

Background:

  • Persistent gaps exist between evidence generation and clinical application in Traditional Chinese Medicine (TCM).
  • Existing frameworks struggle to accommodate TCM's holistic perspective and pattern-based diagnosis/therapy.
  • Qian Xuesen's theory of open complex giant systems (OCGSs) provides a foundation for a new approach.

Purpose of the Study:

  • To advance a complex-systems evidence framework tailored for Traditional Chinese Medicine (TCM).
  • To integrate qualitative and quantitative approaches for evidence generation and clinical use.
  • To improve clinical decision quality and accelerate translational research in TCM.

Main Methods:

  • Utilized Qian Xuesen's theory of open complex giant systems (OCGSs) and qualitative-to-quantitative metasynthesis.
  • Developed a four-phase evidence loop: production, differentiation, application, and validation.
  • Integrated systems science, artificial intelligence, and allied disciplines for evidence coordination.

Main Results:

  • The framework organizes multi-source evidence into a standardized production, integrated evaluation, individualized application, and feedback-driven validation loop.
  • It links clinical phenotypes, pathways, and outcomes into a cohesive evidence chain.
  • The framework facilitates macro-level effectiveness evaluation aligned with micro-level mechanistic inquiry.

Conclusions:

  • The proposed framework addresses TCM's unique characteristics, improving clinical decision-making and translational research.
  • It offers a generalizable model for complex interventions within complex human systems.
  • This approach positions TCM research for modernization and international scientific dialogue.