EJHP booklet for EAHP 2024

Original research

Toward a better understanding about real- world evidence Mei Liu, 1,2,3 Yana Qi, 1,2,3 Wen Wang, 1,2,3 Xin Sun 1,2,3

1 Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu, China 2 NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu, China 3 Sichuan Center of Technology Innovation for Real World Data, Chengdu, China Correspondence to Professor Xin Sun, Sichuan University, Chengdu 610041, China; sunxin@wchscu.cn Received 29 September 2021 Accepted 3 November 2021 Published Online First 2 December 2021 EAHP Statement 6: Education and Research.

In reality, the methodological framework for RWE is more complex than classical clinical trials. Lack of strong methodological and statistical expertise may sometimes lead to inappropriate handling of data, thus producing unreliable or even incorrect conclu- sions. 3 Therefore, it is important to better understand the concept and methodological issues regarding RWE. CONCEPTUAL FRAMEWORK OF REAL-WORLD EVIDENCE The term ‘real-world evidence’ is often used to refer to clinical evidence about utilisation (eg, treat- ment pattern or compliance), benefits and harms of medical products in a defined population or a subgroup population. The evidence is typically derived from analyses of healthcare data outside of classical clinical trials. 2 Data sources for generating RWE usually come in two main forms, including routinely collected healthcare data (RCD) and actively collected healthcare data in routine clinical practice settings. 4 While RCD are often generated from routine prac- tice for non-research purposes, such as electronic medical records, claims data and health surveillance data, actively collected healthcare data are often collected with certain research purposes. These two forms of data are important sources of real-world data, and their common features are that the data are derived from routine clinical practice. RWE is derived from the analyses of real-world data, and in many cases is based on observational study designs. However, such studies are suscep- tible to bias due to the complexity in the health- care setting, data, and observational nature of the design. Both researchers and evidence users must be highly cautious about observational studies using real-world data. It is also worth noting that RWE is not equivalent to observational study. An interventional study can also be used to generate RWE, and one such design is a pragmatic clinical trial. 3 5 This study design is often prioritised where the treatment effect on a heterogeneous population is urgently needed, the optimal treatment is largely unknown in routine practice, or medical needs (typically those related to patient welfare) are insuf- ficiently met. 6 In this paper, we specifically discuss issues about observational studies using real-world data, especially routinely collected healthcare data. ISSUES ABOUT DATA SOURCES: FOCUSING ON ROUTINELY COLLECTED DATA Routinely collected healthcare data represent the most common type of real-world data. Because these data are typically collected in routine

ABSTRACT Background 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. Methods 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. Results 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. Conclusions 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. In recent years, the concept of real-world evidence (RWE) has become widely accepted. In particular, with the release of the 21st Century Cure Act in the USA, the interest in RWE was fuelled among researchers and policymakers. 1 RWE may have a wide spectrum of applications, such as under- standing about treatment patterns, informing treat- ment outcomes in vulnerable populations, and assessing treatment effects in real-world practice. However, misunderstanding or confusion is still common concerning what RWE is and how one should interpret the evidence. For example, a common misconception about RWE is that it can only be generated using data from routine clinical care and does not involve new data collection over a pre-defined protocol. 2 Another common miscon- ception is that RWE merely refers to evidence generated from observational studies. 3

► http://dx.doi.org/10.1136/ ejhpharm-2021-003163

Liu M, et al . Eur J Hosp Pharm 2022; 29 :8–11. doi:10.1136/ejhpharm-2021-003081

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