The development of evidence-based clinical practice guidelines is a sophisticated and systematic process, often requiring multidisciplinary efforts. The traditional approach to developing and updating clinical practice guidelines is usually time-consuming. These limitations obstacle the effective use of guideline recommendations and efficient transformation of most recent research evidence into practice. The MAGIC system is a novel method system for rapid creation and dissemination of high-quality clinical recommendations, including rapid creation of trustworthy recommendations, thus ensuring the scientific and efficient production of clinical practice guidelines; facilitating rapid dissemination and dynamic updating of clinical practice guidelines through recommendation release system (i.e., MAGICapp); and helping promote the production of relevant high-quality original research evidence by identifying the insufficiency of evidence in the process of creation of guideline recommendations. Ultimately, a complete closed-loop digital and trustworthy evidence ecosystem is developed. In order to further promote the effective transformation of research evidence into guideline recommendations, MAGIC China Center was established. We anticipate that the Center will assist the further development and effective use of clinical practice guideline in China.
In 2014, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group published guidance in BMJ to evaluate the certainty of the evidence (confidence in evidence, quality of evidence) from network meta-analysis. GRADE working group suggested rating the certainty of direct evidence, indirect evidence, and network evidence, respectively. Recently, GRADE working group has published a series of papers to improve and supplement this approach. This paper introduces the frontiers and advancement of GRADE approach to rate the certainty of evidence from network meta-analysis.
背景虽然当前已有一些评估卫生保健指南可靠性的工具，但仍缺乏针对制定指南实际步骤的指导。针对指南制定者们所需考虑的相关资源和工具，我们系统研发了一份全面的条目清单，但这并不意味着每篇指南都需遵守该清单的所有条目。 方法我们检索了国际指南制定机构的指南制定手册、指南的指南（主要是来自国际和国家机构以及专业学会的方法学报告），以及提供系统指导的最新文章。经过反复评价这些资料，尽可能全面地罗列和提取条目，并制定与指南有关的重要主题。通过反复讨论，我们对条目进行评价以去重和补漏，同时邀请指南制定专家对所增加的条目进行修改并提出建议。 结果我们制定了一份包含18个主题、146个条目的清单，并建立了帮助指南制定者应用这些条目的网站。这些主题和条目涵盖了指南从规划、完成、实施和评估的全过程。最终的清单版本也包括了培训所需的资料以及应用这些条目时用到的方法学参考文献的链接。 解释本清单将提供给指南制定者用作参考。仔细考虑清单中的条目将有助于指南的制定、实施和评估，我们也将会通过大众反馈来修订并持续更新清单。
With the boom of information technology and data science, real-world evidence (RWE) which is produced using diverse real-world data (RWD) has become an important source for healthcare practice and policy decisions, such as regulatory and coverage decisions, guideline development, and disease management. The production of high-quality RWE requires not only complete, accurate and usable data, but also scientific and sound study designs and data analyses to enable the questions of interest to be reliably answered. In order to improve the quality of production and use of RWE, China REal world data and studies ALliance (ChinaREAL) has developed the first series of technical guidance for developing real-world data and subsequent studies. The efforts are ongoing which would ultimately inform better healthcare practice and policy decisions.