Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu, China.
NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu, China.
Eur J Hosp Pharm. 2022 Jan;29(1):8-11. doi: 10.1136/ejhpharm-2021-003081. Epub 2021 Dec 2.
There has been an interest in real-world evidence (RWE) in recent years. RWE is usually generated from data derived from routine healthcare, such as electronic healthcare records and disease registries. While RWE has many advantages, it is often open to various biases, which may distort results. Appropriate understanding and interpretation are critical to the best use of RWE in healthcare decisions.
On the basis of a literature review and empirical research experience, we summarised the concept and methodological framework of RWE, and discussed in detail methodological issues specific to routinely collected healthcare data and observational studies using such data.
RWE is derived from a spectrum of data generated from the real-world setting, using two broad study designs including observational studies and pragmatic clinical trials. Real-world data may usually be collected through routine practice or sometimes actively collected with a research purpose. Observational studies using routinely collected data (RCD) are the most common type of RWE, although they are prone to biases. When planning and implementing RWE studies, coherent working steps are warranted, including definition of a clear and answerable research question, development of a research team, selection of a fit-for-purpose data source, choice of state-of-the-art study design, establishing a database with transparent data processing, performing multiple statistical analysis to control bias, and reporting results in accordance with established guidelines.
RWE has been mounting over the years. The appropriate interpretation and use of such evidence often warrant adequate understanding about methodology. Researchers and policymakers should be aware of the methodological pitfalls when generating and interpreting RWE.
近年来，人们对真实世界证据（RWE）产生了兴趣。RWE 通常是从常规医疗保健中获得的数据中产生的，例如电子医疗记录和疾病登记处。虽然 RWE 有很多优势，但它通常容易受到各种偏差的影响，这些偏差可能会扭曲结果。适当的理解和解释对于在医疗保健决策中最好地利用 RWE 至关重要。
基于文献综述和实证研究经验，我们总结了 RWE 的概念和方法框架，并详细讨论了使用常规收集的医疗保健数据和基于这些数据的观察性研究的特定方法问题。
RWE 来自于真实世界环境中生成的一系列数据，使用两种广泛的研究设计，包括观察性研究和实用临床试验。真实世界数据通常可以通过常规实践收集，有时也可以有研究目的主动收集。使用常规收集数据（RCD）的观察性研究是最常见的 RWE 类型，尽管它们容易受到偏差的影响。在规划和实施 RWE 研究时，需要有一致的工作步骤，包括定义明确和可回答的研究问题、组建研究团队、选择适合目的的数据来源、选择最先进的研究设计、建立具有透明数据处理的数据库、进行多次统计分析以控制偏差，以及按照既定指南报告结果。
RWE 近年来一直在增加。适当解释和使用这种证据通常需要充分了解方法学。研究人员和政策制定者在生成和解释 RWE 时应该意识到方法学的陷阱。
