New guide aims to help clinicians navigate the expanding landscape of Real-World Data Research

Authored by Alec Thomas and colleagues from institutions in Liverpool, Nairobi and the NIHR Alder Hey Clinical Research Facility, the article outlines the opportunities and issues with using data generated through routine healthcare, such as electronic health records, administrative datasets, and patient registries.

RWD, including resources like the Clinical Practice Research Datalink and Hospital Episode Statistics, now underpins thousands of studies and offers useful insights into patient groups often excluded from clinical trials, such as children and young people from disadvantaged or minority-ethnic backgrounds. 

The authors argue that the ability to link large datasets together has created new avenues for studying rare diseases, long-term outcomes and ethically challenging research questions.

However, the authors also stress that observational research using RWD comes with substantial methodological challenges. These include selection bias (where some populations are over- or under-represented), information bias arising from misclassification or missing data, and confounding, where unmeasured factors distort associations between exposures and outcomes. 

In order to better support clinicians and researchers, the guide highlights existing reporting standards such as the RECORD guidelines and introduces the Assessment of Real World Observational Studies (ArRoWS) critical appraisal tool, which provides nine key questions to help readers assess the robustness of RWD-based observational studies.

The authors also note the importance of looking beyond high-income settings. With many low- and middle-income countries transitioning to electronic health records, the authors argue that strengthening the quality of routinely collected maternal and child health data could unlock important research opportunities, particularly at a time of constrained global health funding.

The guide forms part of a broader series exploring the analytical techniques used with RWD, including interrupted time series and difference-in-differences designs, as well as the role of real-world evidence within randomised controlled trials.

Alec Thomas, whose PhD is funded through the HDR UK Driver Programme, says the aim of this guide is to equip healthcare professionals with the skills to interpret an increasingly complex evidence base. "With the plethora of information available to researchers, it is important that we utilise this for the benefit of those who need it most, whilst also being mindful of the potential pitfalls".

The authors hope the series will support the production of higher-quality research and improve outcomes for children and young people worldwide.

Full citation: Thomas A, Nabwera H, Hawcutt DB, et al. Guide to understanding observational studies that use real-world data. Archives of Disease in Childhood. Published Online First: 06 November 2025. doi:10.1136/archdischild-2025-329491 

https://adc.bmj.com/content/early/2025/11/06/archdischild-2025-329491