BHF Data Science Centre: Data-Enabled Trials Survey Report
- 1. BHF Data Science Centre, Health Data Research UK, London, UK
- 2. BHF Data Science Centre, Health Data Research UK, London, UK; Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- 3. BHF Data Science Centre, Health Data Research UK, London, UK; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
The use of routinely-collected healthcare data in randomised clinical trials offers the potential to deliver more efficient and cost-effective trials. However, it also presents challenges, with a very small proportion (~3%) of clinical trials estimated to be using this data. A major initiative led by the British Heart Foundation (BHF) Data Science Centre, in coordination with Health Data Research UK and NHS DigiTrials, aims to streamline data-enabled cardiovascular clinical trials.
To investigate the use of routinely-collected data in cardiovascular disease (CVD) clinical trials, we carried out a survey to identify trialists and CVD clinical trials using or planning to use routinely-collected data, and explore the challenges faced. The survey results highlight clear barriers to the use of routinely collected data. Respondents reported challenges with ease and timeliness of data access, and with data availability, with many difficulties arising from the processes and bureaucracy (both real and perceived) involved in gaining access to data. The survey also identified over 20 CVD clinical trials that are using or planning to use routinely‑collected data, which we are further exploring with a view to identifying trials that we could potentially support as driver projects.
These results will guide the BHF Data Science Centre in where to focus our efforts to best support the cardiovascular clinical trials community, recognising that the challenges are likely to be similar in other disease settings so the impact of our efforts may be generalizable beyond CVD.