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Multi-stakeholder framework to improve clinical research using real-world data

Framework proposes how to more effectively use and disseminate routine healthcare data for clinical research.

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Big data plays a huge role in advancing clinical science that improves patients’ lives around the world. Technological developments have resulted in the routine use of structured electronic healthcare records to fill key gaps in clinical evidence. Research that uses routinely collected, structured healthcare data could make a major impact. However, challenges such as verification, validation and data privacy are limiting the use and acceptance of evidence generated from using structured healthcare data. A well-defined and transparent approach is needed to address these issues.

Framework for an extensive audience of international stakeholders across all disease areas

The EU- and industry-funded BigData Heart project put forward a framework to enhance the reliability and quality of studies that use healthcare data. The approach should also build confidence for those who use the results for clinical decision support. The CODE-EHR Minimum Standards Framework was compiled by many different stakeholders. They mainly included patients, patient advocacy groups, regulators, government agencies and leading medical journals, as well as representatives from professional societies, academic institutions, the pharmaceutical industry and payers. Participants looked at opportunities and challenges and developed practical guidance on how healthcare data can be applied to research across many diseases. BigData Heart coordinated this massive undertaking. The framework was simultaneously published in ‘The BMJ’, ‘The Lancet Digital Health’ and the ‘European Heart Journal’.

More vigorous and efficient use of healthcare data for research

“With the support of patients and the public, routinely collected healthcare information provides an exciting opportunity to answer important clinical questions in populations representative of our communities,” explains lead author Prof. Dipak Kotecha, of project partner University of Birmingham and University Hospitals Birmingham NHS Foundation Trust in the United Kingdom, in a press release posted on the European Society of Cardiology website. “Our ability to apply findings from studies that use these data sources is critically dependent on transparency at every stage. This international framework will enable robust and effective use of healthcare data for clinical research and provide those working in this field with guidance on how to design better studies for maximal benefit to patient care.” The framework offers researchers step-by-step advice for achieving suitable governance and transparency. Various stakeholders will now be able to rely on the reported findings. Minimum standards are set forth for five key areas: data set construction and linkage; data fit for purpose; disease outcome and definitions; analysis; and ethics and governance. Co-author Prof. Folkert Asselbergs, of project coordinator University Medical Center Utrecht, the Netherlands, and project partner University College London, concluded: “The use of real-world data in large-scale registries and randomised trials is ushering in a new era of clinical evidence generation. The CODE-EHR framework addresses public concerns about data sharing and provides greater clarity on the use of real-world healthcare data for a broad range of stakeholders to improve clinical care.” By using novel statistical, machine learning and data mining methodologies, BigData Heart (Big Data 4 Better Hearts - Sofia ref.: 116074) aims to improve patient outcomes and lessen the societal burden of acute coronary syndrome, atrial fibrillation and heart failure. The project ends in February 2023. BigData Heart is supported by the Innovative Medicines Initiative, a partnership between the EU and the European pharmaceutical industry. For more information, please see: BigData Heart project website

Keywords

BigData Heart, data, healthcare, healthcare data, big data, framework, patient, clinical research