The shift from paper to electronic health records provides many opportunities in clinical research – including randomised controlled trials (RCTs). Routine health care data is held widely in national databases or registries including, for example: NHS Digital, ISD Scotland, and SAIL. Said data can be used to replace or supplement trial data thereby reducing the resources required for data collection and participant follow-up – in turn reducing trial costs. Likewise, routine health care data serves as a useful starting point for targeted participant recruitment. This is especially important given that many trials struggle to recruit participants and a failure to recruit means some trials must stop early.
Despite being labelled ‘a disruptive technology’, there is little evidence of routinely collected health data use in UK clinical trials. The low rate of uptake considering the cost and time saving benefits, suggests there may be multiple barriers to using registry data. Little research has been done to explore and understand potential blockers.
To help identify possible barriers, HDR UK’s Matthew Sydes and colleagues conducted the first systematic review of RCTs using data from UK-based data registries. The researchers quantified and compared the use of routine health data from 22 data registries across 160 trials – as part of HDR UK’s drive for better, faster, more efficient clinical trials.
What was learned
Only 3% of UK RCTs are leveraging routinely collected health data. But that is not to say that the data is not being used elsewhere – RCTs formed only 2% of the data releases in the registries studied here. A key barrier to access may be a lack of awareness; triallists may not know the data exist, where to find it, and/or how it may be useful in their trials.
Where routine health data has been used by RCTs, it appears that RCTs are often using similar datasets from a limited number of registries; NHS Digital is the most frequently used registry whilst mortality and hospital visits are the most used datasets.
Impact and outcomes
A lack of visibility and accessibility emerged as a key barrier to routine health data use in RCTs. Sydes and colleagues suggest a comprehensive list of accessible data registries, the data they hold, and a public record of approved releases would go some way in increasing uptake by triallists – alongside calls for targeted resources to improve data quality.
As we look to the future of clinical trials, this groundwork is essential in demonstrating the need for initiatives which help the UK realise the full potential of routine health data in RCTs.
Background: Routinely collected health data (RCD) are increasingly used for randomized controlled trials (RCTs). This can provide three major benefits: increasing value through better feasibility (reducing costs, time, and resources), expanding the research agenda (performing trials for research questions otherwise not amenable to trials), and offering novel design and data collection options (e.g., point-of-care trials and other designs directly embedded in routine care). However, numerous hurdles and barriers must be considered pertaining to regulatory, ethical, and data aspects, as well as the costs of setting up the RCD infrastructure. Methodological considerations may be different from those in traditional RCTs: RCD are often collected by individuals not involved in the study and who are therefore blinded to the allocation of trial participants. Another consideration is that RCD trials may lead to greater misclassification biases or dilution effects, although these may be offset by randomization and larger sample sizes. Finally, valuable insights into external validity may be provided when using RCD because it allows pragmatic trials to be performed.
Methods: We provide an overview of the promises, challenges, and potential barriers, methodological implications, and research needs regarding RCD for RCTs.
Results: RCD have substantial potential for improving the conduct and reducing the costs of RCTs, but a multidisciplinary approach is essential to address emerging practical barriers and methodological implications.
Conclusions: Future research should be directed toward such issues and specifically focus on data quality validation, alternative research designs and how they affect outcome assessment, and aspects of reporting and transparency.
Using health data science and large-scale data to improve the lives of people with rare aut...
This project is using national electronic health records to register and improve the health and care of people with rare diseases.
Clinical trials Day 2022: How data can make trials faster, more efficient and better at improving care
20 May 2022
We explore how routinely collected health data may hold the key to super-charging how clinical trials are delivered, and in turn, how quickly we can bring improvements to people's lives.