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 Publication: The CODE-EHR framework

Through greater knowledge of disease and investigation into both current and novel therapies, routinely gathered healthcare data has the potential to enhance the lives and welfare of people all over the world. An international team proposes a framework to enhance the integrity and quality of studies using healthcare data and increase confidence in using the results for clinical decision support. The framework was presented on August 29, 2022, at the ESC Congress and simultaneously published in the European Heart Journal, The BMJ, and The Lancet Digital Health.
It is readily accessible through the following links for you to review:

 CODE-EHR Checklist

Clinical research output and organised healthcare data undergo a complex path. Stakeholder delegates agreed on the necessity for a set of minimum criteria that authors may use as a tool to improve design, reporting, and research output in order to enable continued development in a transparent manner. Authors are allowed to describe how organised healthcare data were used in their research study using the CODE-EHR Minimum Standards Framework, which is shown in table 2 (either in patient identification, disease phenotyping, or outcome derivation). Preferred standards are a sign of high-quality achievement and can be utilised to alter the course of future research.

The path from structured healthcare data to clinical research output is complex. To support further development in a transparent way, stakeholder delegates reached consensus on the need for a set of minimum standards that authors could use as a tool to enhance design, reporting, and research output. The CODE-EHR Minimum Standards Framework accessible in the download link below, allows authors to report on how structured healthcare data were used in their research study (either in patient identification, disease phenotyping, or outcome derivation). Preferred standards indicate high level attainment of quality and can be used as a tool to improve the future trajectory of research.

The checklist, which was developed through an iterative process based on the suggestions from the stakeholders, addresses five crucial areas of increased transparency: the method and justification of coding; the process of building and linking datasets; clear definitions of diseases and outcomes; the approach to analysis, including any computational methods; and demonstrating good data governance.

The CODE-EHR framework checklist is available for download through the links below:

 More about the CODE-EHR approach and framework

The approach was compiled by a wide range of global stakeholders, coordinated by the BigData@Heart consortium and the European Society of Cardiology.  This included patients and patient advocacy groups, regulators, government agencies and leading medical journals, plus representatives from professional societies, academic institutions, the pharmaceutical industry and payers. Participants convened to review opportunities and challenges and develop pragmatic advice on how healthcare data can be applied to research across the spectrum of disease.


 BigData@Heart at ESC2022 Congress in Barcelona

The project was put in the spotlight during an ESC-TV session dedicated to the topic of Challenges and Opportunities of Big Data, which was hosted by Prof. Folkert Asselbergs and featured Prof. Barbara Casadei and Prof. Dipak Kotecha.

Full presentation and slides are accessible on the ESC365 on-demand platform through the link below:

 The ESC and BigData@Heart CODE-EHR framework for using routine healthcare data in clinical research

The Code-EHR framework was introduced on the 29th of August 2022 at the ESC Congress in Barcelona during a symposium chaired by current ESC President, Prof. Franz Weidinger; Prof. Ileana Pina and Prof. Diederick E Grobbee. During this symposium, Professor Folkert Asselbergs from the University Medical Centre Utrecht and Professor Dipak Kotecha from the University of Birmingham presented the current challenges and opportunities to use healthcare data in clinical research and discussed how researchers can use the CODE-EHR framework to enhance and reinforce their research study. 

The full session is accessible on demand on the ESC365 platform through the link below:

 Publication: Patients’ and Publics’ Preferences for Data-Intensive Health Research Governance: Survey Study published

Following a narrative review of empirical evidence on patients’ and public attitudes towards the use of health data for research purposes, BigData@Heart researchers at the University Medical Center Utrecht in collaboration with the European Heart Network, conducted a public survey in 2021 to explore patient and public preferences for concretising data-intensive health research. This study aims to inform efforts to design governance frameworks for data-intensive health research, by gaining insight into the preferences of patients and publics for governance policies and measures.

The findings of this study were published in September 2022 by the JMIR Human Factors journal. Findings point out that policies and measures are crucial for governing health data research and building trust. Due regard should be given to patient and public preference for greater control at the collective level of governance. People have concerns about secondary use of data by commercial parties and the risk of data misuse, reasons for which they favor personal control of their data.

Good governance builds on conditions for support and furthers trustworthiness of health data research.  This message is important for policy makers as they are working towards the development of a European Health Data Space. 

Further research is required to understand how governance policies and measures can contribute to the trustworthiness of data-intensive health research.

Click here to read the paper:
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For more information on BigData@Heart, visit
or contact Pieter Stolk with specific questions.
BigData@Heart is a part of the Big Data for Better Outcomes (BD4BO) programme
The project leading to this application has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 116074. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
Copyright © 2022 BigData@Heart, All rights reserved.

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