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RAND/UCLA适宜性方法中医药评价应用OA

Application of RAND/UCLA Appropriateness Method in Evaluating Chinese Medicine Interventions

中文摘要英文摘要

系统梳理兰德公司/加州大学洛杉矶分校(RAND/UCLA)适宜性研究方法(RAM)的理论基础、实施流程及其在复杂医学干预领域的国际应用经验,并结合慢性颈痛推拿干预的适宜性研究实例,解析该方法如何通过构建结构化临床情境、组织专家多轮评分达成适宜性共识.RAM方法倡导"证据为基、共识为用、情境为实"的适宜性评价范式,从"是否值得提供""是否适合推广"等角度出发,能够补充现有中医药循证体系,可为中医药适宜技术的遴选、规范化、指南制定与推广提供切实可行的研究路径.

The RAND(RAND Corporation)/UCLA(University of California,Los Angeles)appropriateness method(RAM)is a widely applied framework for evaluating complex medical interventions by integrating scientific evidence with expert clinical judgement.This study systematically reviewed the theoretical foundations,procedural steps,and international application of RAM.Using manual therapy for chronic neck pain as an illustrative example,the authors highlighted how RAM facilitated the development of detailed clinical scenarios and guided multi-round experts ratings to reach consensus on treatment appropriateness.Given the individualized,pattern-based diagnostic paradigm of Chinese Medicine(CM),RAM holds particular promise for advancing CM research,particularly in the assessment of appropriate technologies.Unlike approaches that focus solely on effectiveness,RAM incorporated multiple dimensions,including safety,feasibility,patient acceptability,and contextual suitability.These multidimensional perspectives could strengthen the evidence base for CM and contribute to the development of contextually grounded clinical guidelines.This study aims to stimulate discussion on how RAM and similar methodological frameworks can support the modernization,evidence integration,and real-world applicability of CM practice.

吴夏秋;张卫军;吴诗杰;贾丽燕;赵静;季聪华

浙江中医药大学公共卫生学院(杭州 310053)美国加州大学洛杉矶分校东西医学中心(洛杉矶90024)浙江中医药大学公共卫生学院(杭州 310053)浙江中医药大学公共卫生学院(杭州 310053)中国中医科学院中医临床基础医学研究所(北京 100700)浙江中医药大学公共卫生学院(杭州 310053)

适宜性研究RAND/UCLA方法中医药适宜技术循证医学专家共识

appropriateness methodRAND/UCLA Appropriateness MethodChinese Medicineappropriate technologiesevidence based medicineexpert consensus

《中国中西医结合杂志》 2026 (2)

133-138,6

国家科技重大专项课题项目(No.2023ZD0509802)

10.7661/j.cjim.20251228.310

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