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Toward better translation of clinical research evidence into rapid recommendations for traditional Chinese medicine interventions: A methodological framework

Authors :
Li, Qianrui
Luo, Xiaochao
Li, Ling
Ma, Bin
Yao, Minghong
Liu, Jiali
Ge, Long
Chen, Xiaofan
Wu, Xi
Deng, Hongyong
Zhou, Xu
Wen, Zehuai
Li, Guowei
Sun, Xin
Source :
Integrative Medicine Research; September 2022, Vol. 11 Issue: 3
Publication Year :
2022

Abstract

Rapid recommendation is a novel methodological framework for developing clinical practice guidelines and this framework shares the basic features of classical guidelines but differs from classical clinical practice guidelines in its `rapid’ development process (typically within 90 days) with an aim of translating practice-changing studies to recommendations. A recent global innovation of guideline development methodology is the proposal of a rapid recommendation framework for Traditional Chinese Medicine (TCM), which has the potential to add value to the translation of evidence to practice for TCM interventions. Up to now, more than 180 rapid recommendations have been published, but none of them is pertaining to TCM interventions. Due to the nature of multi-dimensional evidence sources for TCM interventions, including classical randomized controlled trials and real world evidence, a more sophisticated methodological approach to synthesize and evaluate the totality of evidence about effects of TCM interventions is required. Therefore, appropriate modification to the rapid recommendation framework is necessary. In the efforts to respond to these needs, we have proposed a specific approach to developing rapid recommendations for TCM interventions the Multi-dimensional Evidence Synthesis, Evaluation and Recommendations for TCM interventions (MESERT).

Details

Language :
English
ISSN :
22134220 and 22134239
Volume :
11
Issue :
3
Database :
Supplemental Index
Journal :
Integrative Medicine Research
Publication Type :
Periodical
Accession number :
ejs59099837
Full Text :
https://doi.org/10.1016/j.imr.2022.100841