Related Experiment Video
Updated: Aug 6, 2025
In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
Healthcare systems data in the context of clinical trials - A comparison of cardiovascular data from a clinical trial
Archie Macnair1, Matthew Nankivell2, Macey L Murray3
1MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK; Health Data Research, UK; Guys and St Thomas' NHS Foundation Trust, London, UK.
Insights
Healthcare system data (HSD) shows low concordance with clinical trial data for cardiovascular events. Routine data cannot yet replace current trial practices, requiring further work to improve HSD quality and event definitions.
Area of Science:
- Cardiovascular Research
- Health Informatics
- Clinical Trial Methodology
Background:
- Routinely-collected healthcare systems data (HSD) offers potential for enhancing clinical trial efficiency.
- A comparative analysis was performed between cardiovascular (CVS) data from a clinical trial database and two HSD resources.
Purpose of the Study:
- To assess the feasibility of using HSD to identify protocol-defined cardiovascular events in clinical trials.
- To compare the concordance between clinical trial data and HSD (NHS Hospital Episode Statistics and NICOR audits).
Main Methods:
- Identified protocol-defined CVS events (heart failure, acute coronary syndrome, etc.) within trial data.
- Obtained data from NHS Hospital Episode Statistics (HES) and NICOR audits for consenting trial participants (2010-2018).
- Compared trial data with HES inpatient main diagnosis and explored reasons for discrepancies.
Main Results:
- Out of 1200 participants, 71 CVS events were in the trial database; 45 required hospital admission.
- Only 60% (27/45) of hospital-admitted events were recorded in HES inpatient data.
- Heart failure and acute coronary syndrome events showed varied recording across trial data (18), HES APC (29), and NICOR (24), with 67% concordance between trial and NICOR data.
Conclusions:
- The concordance between HSD and clinical trial data for cardiovascular events was lower than expected.
- Current HSD resources cannot directly replace established clinical trial data collection methods for protocol-defined events.
- Future research should focus on improving HSD quality and refining event definitions for trials integrating HSD.
Background:
Routinely-collected healthcare systems data (HSD) are proposed to improve the efficiency of clinical trials. A comparison was undertaken between cardiovascular (CVS) data from a clinical trial database with two HSD resources.
Methods:
Protocol-defined and clinically reviewed CVS events (heart failure (HF), acute coronary syndrome (ACS), thromboembolic stroke, venous and arterial thromboembolism) were identified within the trial data. Data (using pre-specified codes) was obtained from NHS Hospital Episode Statistics (HES) and National Institute for Cardiovascular Outcomes Research (NICOR) HF and myocardial ischaemia audits for trial participants recruited in England between 2010 and 2018 who had provided consent. The primary comparison was trial data versus HES inpatient (APC) main diagnosis (Box-1). Correlations are presented with descriptive statistics and Venn diagrams. Reasons for non-correlation were explored.
Results:
From 1200 eligible participants, 71 protocol-defined clinically reviewed CVS events were recorded in the trial database. 45 resulted in a hospital admission and therefore could have been recorded by either HES APC/ NICOR. Of these, 27/45 (60%) were recorded by HES inpatient (Box-1) with an additional 30 potential events also identified. HF and ACS were potentially recorded in all 3 datasets; trial data recorded 18, HES APC 29 and NICOR 24 events respectively. 12/18 (67%) of the HF/ACS events in the trial dataset were recorded by NICOR.
Conclusion:
Concordance between datasets was lower than anticipated and the HSD used could not straightforwardly replace current trial practices, nor directly identify protocol-defined CVS events. Further work is required to improve the quality of HSD and consider event definitions when designing clinical trials incorporating HSD.
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