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Published July 20, 2023 | Version 1.0
Report Open

Standardising Clinical Outcome measures in Routinely-collected Electronic healthcare systems data (SCORE-CVD) Initial Report

  • 1. BHF Data Science Centre, Health Data Research UK, MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College, London
  • 2. BHF Data Science Centre, Health Data Research UK, Usher Institute, Edinburgh University Medical School, Centre for Clinical Brain Sciences, University of Edinburgh
  • 3. BHF Data Science Centre, Institute of Health Informatics, University College London
  • 4. BHF Data Science Centre, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield.
  • 5. BHF Data Science Centre
  • 6. Robertson Centre for Biostatistics, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
  • 7. Institute of Health Informatics, University College London, University College London Hospitals NHS Trust
  • 8. Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
  • 9. 1) Leeds Institute for CardioVascular and Metabolic Medicine, University of Leeds, Leeds, UK 2) Leeds Institute of Data Analytics, University of Leeds, Leeds, UK 3) Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
  • 10. Division of Cardiovascular Sciences, University of Manchester
  • 11. Centre for Cardiovascular Science, University of Edinburgh
  • 12. Academic Cardiovascular Unit (ACU), South Tees NHS Trust, University of Newcastle
  • 13. Division of Informatics, Imaging & Data Sciences, University of Manchester
  • 14. University of Leicester
  • 15. 1 Institute of Health Informatics, University College London, London, United Kingdom 2 Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Amsterdam, The Netherlands
  • 16. Department of Cardiovascular Sciences University of Leicester
  • 17. University of Oxford
  • 18. School of Public Health & National Heart and Lung Institute, Imperial College London, London, UK
  • 19. Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge. UK.
  • 20. Primary Care Unit, Department of Public Health & Primary Care, University of Cambridge, Cambridge UK
  • 21. Leicester Diabetes Centre, University of Leicester
  • 22. Deep Medicine, Nuffield Department of Women's and Reproductive Health, University of Oxford
  • 23. Division of Clinical Neurosciences, University of Edinburgh
  • 24. Cardiology, Liverpool Heart and Chest Hospital, Thomas Drive, Liverpool, UK.
  • 25. Keele Cardiovascular Research Group, Keele University, UK
  • 26. Clinical Trials and Evaluation Unit, University of Bristo
  • 27. Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) at Oxford Population Health, University of Oxford
  • 28. Institute of Cardiovascular and Medical Sciences, University of Glasgow
  • 29. Clinical Trials Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
  • 30. Barts Heart Centre, University College London
  • 31. Institute of Cardiovascular and Metabolic Medicine, University of Leeds
  • 32. Academic Cardiovascular Unit, South Tees Hospitals NHS Foundation Trust, University of Newcastle
  • 33. 1. Division of Clinical Medicine, University of Sheffield, Sheffield, United Kingdom 2. NIHR Sheffield Biomedical Research Centre, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom
  • 34. Cardiovascular & Metabolic Medicine, University of Liverpool
  • 35. Population Health Research, University of Glasgow
  • 36. Centre for Clinical Brain Sciences, Edinburgh Clinical Trials Unit, Usher Institute of Population Health Sciences and Informatics, Edinburgh
  • 37. MRC Epidemiology Unit, University of Cambridge
  • 38. Department of Public Health and Primary Care, University of Cambridge
  • 39. Institute of Health Informatics, University College London
  • 40. University of Edinburgh

Description

The use of routinely-collected healthcare data (also known as electronic health records) 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.

The Data-Enabled Trials area within the BHF Data Science Centre (BHF DSC) would like to make it easier for researchers and clinicians to safely and securely access electronic health records to support, or replace data that is collected just for a clinical trial. We want to facilitate this transformation in the way clinical trials can be done.

The SCORE-CVD project aims to define community-agreed best practices for the derivation, format, and storage of phenotyping algorithms using Electronic Health Records (healthcare systems datasets [HSD]) for commonly used clinical trial outcome measures. Phenotyping algorithms are computable instructions that use the information contained within healthcare systems datasets to identify people with, or who have experienced, a specific clinical event/disease or characteristic.

The SCORE-CVD project is led by members of BHF DSC, and delivered by working with a Steering Group and a number of outcome-specific ‘Task and Finish’ Groups focusing on the following areas:

  • Phenotyping algorithm requirements
  • Myocardial Infarction
  • Stroke
  • Major Bleeding
  • Heart failure
  • Death/Mortality

This report covers findings from the initial round of workshops from all groups and details plans for the next steps for SCORE-CVD.

 

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Score-CVD Initial report 2023.07.20 v1.0.pdf

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