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Kurihara C, Greco D, Dhai A, Matsuyama K, Baroutsou V. Vulnerability, social value and the equitable sharing of benefits from research: beyond the placebo and access debates. Front Med (Lausanne) 2024; 11:1432267. [PMID: 39355849 PMCID: PMC11442373 DOI: 10.3389/fmed.2024.1432267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 08/28/2024] [Indexed: 10/03/2024] Open
Abstract
The vulnerability of research participants is a critical topic for the 2024 revision of the Declaration of Helsinki, with the proposal to include "social value. " However, this proposal has been withdrawn and the relationship between the two concepts has not been clarified. This paper attempts to clarify: (1) the recent reform for the ethical inclusion of vulnerable study participants to promote diversity; (2) the social value, prerequisite for everyone, especially for those who are vulnerable and the most in need; (3) the requirements for promoting the inclusion of vulnerable participants, in particular the review of the norms for placebo-controlled trials and post-trial access; (4) finally, the direction of research ethics reform to achieve social value and equitable global health.
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Affiliation(s)
- Chieko Kurihara
- Kanagawa Dental University, Yokosuka, Japan
- Ethics Working Group of International Federation of Associations of Pharmaceutical Physicians and Pharmaceutical Medicine (IFAPP), Woerden, Netherlands
| | - Dirceu Greco
- School of Medicine, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Ames Dhai
- School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa
| | - Kotone Matsuyama
- Ethics Working Group of International Federation of Associations of Pharmaceutical Physicians and Pharmaceutical Medicine (IFAPP), Woerden, Netherlands
- Department of Health Policy and Management, Nippon Medical School, Tokyo, Japan
| | - Varvara Baroutsou
- Ethics Working Group of International Federation of Associations of Pharmaceutical Physicians and Pharmaceutical Medicine (IFAPP), Woerden, Netherlands
- International Federation of Associations of Pharmaceutical Physicians and Pharmaceutical Medicine (IFAPP) President, Woerden, Netherlands
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2
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Teodorowski P, Jones E, Tahir N, Ahmed S, Rodgers SE, Frith L. Public Involvement and Engagement in Big Data Research: Scoping Review. J Particip Med 2024; 16:e56673. [PMID: 39150751 PMCID: PMC11364952 DOI: 10.2196/56673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 05/06/2024] [Accepted: 06/22/2024] [Indexed: 08/17/2024] Open
Abstract
BACKGROUND The success of big data initiatives depends on public support. Public involvement and engagement could be a way of establishing public support for big data research. OBJECTIVE This review aims to synthesize the evidence on public involvement and engagement in big data research. METHODS This scoping review mapped the current evidence on public involvement and engagement activities in big data research. We searched 5 electronic databases, followed by additional manual searches of Google Scholar and gray literature. In total, 2 public contributors were involved at all stages of the review. RESULTS A total of 53 papers were included in the scoping review. The review showed the ways in which the public could be involved and engaged in big data research. The papers discussed a broad range of involvement activities, who could be involved or engaged, and the importance of the context in which public involvement and engagement occur. The findings show how public involvement, engagement, and consultation could be delivered in big data research. Furthermore, the review provides examples of potential outcomes that were produced by involving and engaging the public in big data research. CONCLUSIONS This review provides an overview of the current evidence on public involvement and engagement in big data research. While the evidence is mostly derived from discussion papers, it is still valuable in illustrating how public involvement and engagement in big data research can be implemented and what outcomes they may yield. Further research and evaluation of public involvement and engagement in big data research are needed to better understand how to effectively involve and engage the public in big data research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-https://doi.org/10.1136/bmjopen-2021-050167.
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Affiliation(s)
- Piotr Teodorowski
- Faculty of Health Sciences and Sport, University of Stirling, Stirling, United Kingdom
| | - Elisa Jones
- Department of Public Health, Policy & Systems, University of Liverpool, Liverpool, United Kingdom
| | - Naheed Tahir
- National Institute for Health and Care Research Applied Research Collaboration North West Coast, Liverpool, United Kingdom
| | - Saiqa Ahmed
- National Institute for Health and Care Research Applied Research Collaboration North West Coast, Liverpool, United Kingdom
| | - Sarah E Rodgers
- Department of Public Health, Policy & Systems, University of Liverpool, Liverpool, United Kingdom
| | - Lucy Frith
- Centre for Social Ethics and Policy, University of Manchester, Manchester, United Kingdom
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Staunton C, Shabani M, Mascalzoni D, Mežinska S, Slokenberga S. Ethical and social reflections on the proposed European Health Data Space. Eur J Hum Genet 2024; 32:498-505. [PMID: 38355959 PMCID: PMC11061131 DOI: 10.1038/s41431-024-01543-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 11/08/2023] [Accepted: 01/15/2024] [Indexed: 02/16/2024] Open
Abstract
The COVID-19 pandemic demonstrated the benefits of international data sharing. Data sharing enabled the health care policy makers to make decisions based on real-time data, it enabled the tracking of the virus, and importantly it enabled the development of vaccines that were crucial to mitigating the impact of the virus. This data sharing is not the norm as data sharing needs to navigate complex ethical and legal rules, and in particular, the fragmented application of the General Data Protection Regulation (GDPR). The introduction of the draft regulation for a European Health Data Space (EHDS) in May 2022 seeks to address some of these legal issues. If passed, it will create an obligation to share electronic health data for certain secondary purposes. While there is a clear need to address the legal complexities involved with data sharing, it is critical that any proposed reforms are in line with ethical principles and the expectations of the data subjects. In this paper we offer a critique of the EHDS and offer some recommendations for this evolving regulatory space.
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Affiliation(s)
- Ciara Staunton
- Institute for Biomedicine, Eurac Research, Bolzano, Italy.
- School of Law, University of Kwazulunatal, Durban, South Africa.
| | - Mahsa Shabani
- Faculty of Law and Criminology, Ghent University, Gent, Belgium
| | - Deborah Mascalzoni
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
- Department of Public Health and Caring Science, Uppsala University, CRB, P.O. Box 256, 751 05, Uppsala, Sweden
| | - Signe Mežinska
- Institute of Clinical and Preventive Medicine, University of Latvia, Riga, Latvia
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Hallinan CM, Ward R, Hart GK, Sullivan C, Pratt N, Ng AP, Capurro D, Van Der Vegt A, Liaw ST, Daly O, Luxan BG, Bunker D, Boyle D. Seamless EMR data access: Integrated governance, digital health and the OMOP-CDM. BMJ Health Care Inform 2024; 31:e100953. [PMID: 38387992 PMCID: PMC10882353 DOI: 10.1136/bmjhci-2023-100953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 01/14/2024] [Indexed: 02/24/2024] Open
Abstract
Objectives In this overview, we describe theObservational Medical Outcomes Partnership Common Data Model (OMOP-CDM), the established governance processes employed in EMR data repositories, and demonstrate how OMOP transformed data provides a lever for more efficient and secure access to electronic medical record (EMR) data by health service providers and researchers.Methods Through pseudonymisation and common data quality assessments, the OMOP-CDM provides a robust framework for converting complex EMR data into a standardised format. This allows for the creation of shared end-to-end analysis packages without the need for direct data exchange, thereby enhancing data security and privacy. By securely sharing de-identified and aggregated data and conducting analyses across multiple OMOP-converted databases, patient-level data is securely firewalled within its respective local site.Results By simplifying data management processes and governance, and through the promotion of interoperability, the OMOP-CDM supports a wide range of clinical, epidemiological, and translational research projects, as well as health service operational reporting.Discussion Adoption of the OMOP-CDM internationally and locally enables conversion of vast amounts of complex, and heterogeneous EMR data into a standardised structured data model, simplifies governance processes, and facilitates rapid repeatable cross-institution analysis through shared end-to-end analysis packages, without the sharing of data.Conclusion The adoption of the OMOP-CDM has the potential to transform health data analytics by providing a common platform for analysing EMR data across diverse healthcare settings.
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Affiliation(s)
- Christine Mary Hallinan
- Health and Biomedical Informatics Centre, Research Information Technology Unit (HaBIC R2), Department of General Practice and Primary Care, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Roger Ward
- Health and Biomedical Informatics Centre, Research Information Technology Unit (HaBIC R2), Department of General Practice and Primary Care, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Graeme K Hart
- School of Computing and Information Systems, Faculty of Engineering and Information Technology, Centre for the Digital Transformation of Health, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Clair Sullivan
- Queensland Digital Health Centre (QDHeC), Centre for Health Services Research, The University of Queensland Faculty of Medicine, Woolloongabba, Queensland, Australia
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Ashley P Ng
- Clinical Haematology Department, The Royal Melbourne Hospital, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Daniel Capurro
- School of Computing and Information Systems, Faculty of Engineering and Information Technology, Centre for the Digital Transformation of Health, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
- Department of General Medicine, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Anton Van Der Vegt
- Queensland Digital Health Centre (QDHeC), Centre for Health Services Research, The University of Queensland Faculty of Medicine, Herston, Queensland, Australia
| | - Siaw-Teng Liaw
- School of Population Health, UNSW, Sydney, New South Wales, Australia
| | - Oliver Daly
- School of Computing and Information Systems, Faculty of Engineering and Information Technology, Centre for the Digital Transformation of Health, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Blanca Gallego Luxan
- Centre for Big Data Research in Health (CBDRH), UNSW, Sydney, New South Wales, Australia
| | - David Bunker
- Queensland Digital Health Centre (QDHeC), Centre for Health Services Research, The University of Queensland Faculty of Medicine, Herston, Queensland, Australia
| | - Douglas Boyle
- Health and Biomedical Informatics Centre, Research Information Technology Unit (HaBIC R2), Department of General Practice and Primary Care, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
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Hollestelle MJ, van der Graaf R, Sturkenboom MCJM, Cunnington M, van Delden JJM. Building a Sustainable Learning Health Care System for Pregnant and Lactating People: Interview Study Among Data Access Providers. JMIR Pediatr Parent 2024; 7:e47092. [PMID: 38329780 PMCID: PMC10884907 DOI: 10.2196/47092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 11/16/2023] [Accepted: 11/29/2023] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND In many areas of health care, learning health care systems (LHSs) are seen as promising ways to accelerate research and outcomes for patients by reusing health and research data. For example, considering pregnant and lactating people, for whom there is still a poor evidence base for medication safety and efficacy, an LHS presents an interesting way forward. Combining unique data sources across Europe in an LHS could help clarify how medications affect pregnancy outcomes and lactation exposures. In general, a remaining challenge of data-intensive health research, which is at the core of an LHS, has been obtaining meaningful access to data. These unique data sources, also called data access providers (DAPs), are both public and private organizations and are important stakeholders in the development of a sustainable and ethically responsible LHS. Sustainability is often discussed as a challenge in LHS development. Moreover, DAPs are increasingly expected to move beyond regulatory compliance and are seen as moral agents tasked with upholding ethical principles, such as transparency, trustworthiness, responsibility, and community engagement. OBJECTIVE This study aims to explore the views of people working for DAPs who participate in a public-private partnership to build a sustainable and ethically responsible LHS. METHODS Using a qualitative interview design, we interviewed 14 people involved in the Innovative Medicines Initiative (IMI) ConcePTION (Continuum of Evidence from Pregnancy Exposures, Reproductive Toxicology and Breastfeeding to Improve Outcomes Now) project, a public-private collaboration with the goal of building an LHS for pregnant and lactating people. The pseudonymized transcripts were analyzed thematically. RESULTS A total of 3 themes were identified: opportunities and responsibilities, conditions for participation and commitment, and challenges for a knowledge-generating ecosystem. The respondents generally regarded the collaboration as an opportunity for various reasons beyond the primary goal of generating knowledge about medication safety during pregnancy and lactation. Respondents had different interpretations of responsibility in the context of data-intensive research in a public-private network. Respondents explained that resources (financial and other), scientific output, motivation, agreements collaboration with the pharmaceutical industry, trust, and transparency are important conditions for participating in and committing to the ConcePTION LHS. Respondents also discussed the challenges of an LHS, including the limitations to (real-world) data analyses and governance procedures. CONCLUSIONS Our respondents were motivated by diverse opportunities to contribute to an LHS for pregnant and lactating people, primarily centered on advancing knowledge on medication safety. Although a shared responsibility for enabling real-world data analyses is acknowledged, their focus remains on their work and contribution to the project rather than on safeguarding ethical data handling. The results of our interviews underline the importance of a transparent governance structure, emphasizing the trust between DAPs and the public for the success and sustainability of an LHS.
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Affiliation(s)
- Marieke J Hollestelle
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Bioethics & Health Humanities, University Medical Center Utrecht, Utrecht, Netherlands
| | - Rieke van der Graaf
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Bioethics & Health Humanities, University Medical Center Utrecht, Utrecht, Netherlands
| | - Miriam C J M Sturkenboom
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Data Science & Biostatistics, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Johannes J M van Delden
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Bioethics & Health Humanities, University Medical Center Utrecht, Utrecht, Netherlands
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Braunack‐Mayer AJ, Adams C, Nettel‐Aguirre A, Fabrianesi B, Carolan L, Beilby J, Flack F. Community views on the secondary use of general practice data: Findings from a mixed-methods study. Health Expect 2024; 27:e13984. [PMID: 38361335 PMCID: PMC10869884 DOI: 10.1111/hex.13984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 09/29/2023] [Accepted: 01/23/2024] [Indexed: 02/17/2024] Open
Abstract
INTRODUCTION General practice data, particularly when combined with hospital and other health service data through data linkage, are increasingly being used for quality assurance, evaluation, health service planning and research. In this study, we explored community views on sharing general practice data for secondary purposes, including research, to establish what concerns and conditions need to be addressed in the process of developing a social licence to support such use. METHODS We used a mixed-methods approach with focus groups (November-December 2021), followed by a cross-sectional survey (March-April 2022). RESULTS The participants in this study strongly supported sharing general practice data with the clinicians responsible for their care, and where there were direct benefits for individual patients. Over 90% of survey participants (N = 2604) were willing to share their general practice information to directly support their health care, that is, for the primary purpose of collection. There was less support for sharing data for secondary purposes such as research and health service planning (36% and 45% respectively in broad agreement) or for linking general practice data to data in the education, social services and criminal justice systems (30%-36%). A substantial minority of participants were unsure or could not see how benefits would arise from sharing data for secondary purposes. Participants were concerned about the potential for privacy breaches, discrimination and data misuse and they wanted greater transparency and an opportunity to consent to data release. CONCLUSION The findings of this study suggest that the public may be more concerned about sharing general practice data for secondary purposes than they are about sharing data collected in other settings. Sharing general practice data more broadly will require careful attention to patient and public concerns, including focusing on the factors that will sustain trust and legitimacy in general practice and GPs. PATIENT AND PUBLIC CONTRIBUTION Members of the public were participants in the study. Data produced from their participation generated study findings. CLINICAL TRIAL REGISTRATION Not applicable.
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Affiliation(s)
- Annette J. Braunack‐Mayer
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and Society, Faculty of the Arts, Social Sciences and HumanitiesUniversity of WollongongWollongongNew South WalesAustralia
- Australia Health Services Research InstituteUniversity of WollongongWollongongNew South WalesAustralia
| | - Carolyn Adams
- Macquarie Law SchoolMacquarie UniversitySydneyNew South WalesAustralia
| | - Alberto Nettel‐Aguirre
- National Institute for Applied Statistics Research AustraliaUniversity of WollongongWollongongNew South WalesAustralia
| | - Belinda Fabrianesi
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and Society, Faculty of the Arts, Social Sciences and HumanitiesUniversity of WollongongWollongongNew South WalesAustralia
| | - Lucy Carolan
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and Society, Faculty of the Arts, Social Sciences and HumanitiesUniversity of WollongongWollongongNew South WalesAustralia
| | - Justin Beilby
- School of Health and SocietyUniversity of WollongongWollongongNew South WalesAustralia
| | - Felicity Flack
- Population Health Research NetworkUniversity of Western AustraliaPerthWestern AustraliaAustralia
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7
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Lieneck C, Pacheco G, Cole M, Hipp L, Leal G, Matamoros K, Rojas-Trejo B, Stepp N, Torres C. Patient Co-Creation Initiatives in the Ambulatory Care Setting during COVID-19: A Systematic Review. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:111. [PMID: 38256372 PMCID: PMC10818531 DOI: 10.3390/medicina60010111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/24/2024]
Abstract
Background and Objectives: The COVID-19 pandemic has led to significant changes in ambulatory care to meet new healthcare demands. Materials and Methods: A review of 21 articles focusing on patient co-creation initiatives during the pandemic shows that integrating patient feedback was crucial in transforming care delivery. Results: Joint efforts between healthcare professionals and patients led to new patient-focused telemedicine platforms, more efficient appointment systems, and improved safety measures. These adaptations overcame care barriers and maintained continuity of care. Key themes identified include monitoring community health standards, combining technology with patient-provider communication, and enhancing patient participation in health research. Conclusions: These co-creation efforts not only boosted patient satisfaction and outcomes but also demonstrated the potential for long-term healthcare innovations beyond the pandemic. The review further illuminates that co-creation in healthcare, particularly in tracking community health trends, is a practical strategy that involves diverse stakeholders in shaping healthcare delivery. The widespread adoption of co-creation in outpatient care during the pandemic highlights its role in driving patient-centered behavioral changes through innovative methods like crowdsourcing and dialogue conferencing. The review also recognizes that co-creation has been instrumental in responding to demographic changes, enhancing resources, creativity, and problem-solving in municipal-volunteer collaborations. Additionally, the evolution of technology in patient-provider communication, from initial resistance in the 1990s to its current critical role, particularly during the COVID-19 pandemic, underscores its importance in enhancing healthcare service delivery and patient data communication. The review also emphasizes the need for ethically and accessibly designed technology, especially for vulnerable groups, and highlights the significance of patient involvement in healthcare research, advocating for user-centered design and shared decision-making to create truly patient-centric interventions.
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Affiliation(s)
- Cristian Lieneck
- School of Health Administration, Texas State University, San Marcos, TX 78666, USA; (G.P.); (M.C.); (L.H.); (G.L.); (K.M.); (B.R.-T.); (N.S.); (C.T.)
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Schröder M, Muller SH, Vradi E, Mielke J, Lim YM, Couvelard F, Mostert M, Koudstaal S, Eijkemans MJ, Gerlinger C. Sharing Medical Big Data While Preserving Patient Confidentiality in Innovative Medicines Initiative: A Summary and Case Report from BigData@Heart. BIG DATA 2023; 11:399-407. [PMID: 37889577 PMCID: PMC10733752 DOI: 10.1089/big.2022.0178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/29/2023]
Abstract
Sharing individual patient data (IPD) is a simple concept but complex to achieve due to data privacy and data security concerns, underdeveloped guidelines, and legal barriers. Sharing IPD is additionally difficult in big data-driven collaborations such as Bigdata@Heart in the Innovative Medicines Initiative, due to competing interests between diverse consortium members. One project within BigData@Heart, case study 1, needed to pool data from seven heterogeneous data sets: five randomized controlled trials from three different industry partners, and two disease registries. Sharing IPD was not considered feasible due to legal requirements and the sensitive medical nature of these data. In addition, harmonizing the data sets for a federated data analysis was difficult due to capacity constraints and the heterogeneity of the data sets. An alternative option was to share summary statistics through contingency tables. Here it is demonstrated that this method along with anonymization methods to ensure patient anonymity had minimal loss of information. Although sharing IPD should continue to be encouraged and strived for, our approach achieved a good balance between data transparency while protecting patient privacy. It also allowed a successful collaboration between industry and academia.
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Affiliation(s)
- Megan Schröder
- The Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-Universität München, Münich, Germany
| | - Sam H.A. Muller
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Eleni Vradi
- Biomedical Data Science II, Bayer AG, Berlin, Germany
| | - Johanna Mielke
- Research and Early Development, Bayer AG, Wuppertal, Germany
| | - Yvonne M.F. Lim
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Institute for Clinical Research, National Institutes of Health, Selangor, Malaysia
| | - Fabrice Couvelard
- Institut de Recherches Internationales SERVIER (I.R.I.S.), Suresnes, France
| | - Menno Mostert
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Stefan Koudstaal
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Division of Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Cardiology, Groene Hart Ziekenhuis, Gouda, The Netherlands
| | - Marinus J.C. Eijkemans
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Christoph Gerlinger
- Clinical Statistics and Data Insights, Bayer AG, Berlin, Germany
- Department of Gynecology, Obstetrics and Reproductive Medicine, University Medical School of Saarland, Homburg/Saar, Germany
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Yu J, Shen N, Conway S, Hiebert M, Lai-Zhao B, McCann M, Mehta RR, Miranda M, Putterman C, Santisteban JA, Thomson N, Young C, Chiuccariello L, Hunter K, Hill S. A holistic approach to integrating patient, family, and lived experience voices in the development of the BrainHealth Databank: a digital learning health system to enable artificial intelligence in the clinic. FRONTIERS IN HEALTH SERVICES 2023; 3:1198195. [PMID: 37927443 PMCID: PMC10625404 DOI: 10.3389/frhs.2023.1198195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/04/2023] [Indexed: 11/07/2023]
Abstract
Artificial intelligence, machine learning, and digital health innovations have tremendous potential to advance patient-centred, data-driven mental healthcare. To enable the clinical application of such innovations, the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health, Canada's largest mental health hospital, embarked on a journey to co-create a digital learning health system called the BrainHealth Databank (BHDB). Working with clinicians, scientists, and administrators alongside patients, families, and persons with lived experience (PFLE), this hospital-wide team has adopted a systems approach that integrates clinical and research data and practices to improve care and accelerate research. PFLE engagement was intentional and initiated at the conception stage of the BHDB to help ensure the initiative would achieve its goal of understanding the community's needs while improving patient care and experience. The BHDB team implemented an evolving, dynamic strategy to support continuous and active PFLE engagement in all aspects of the BHDB that has and will continue to impact patients and families directly. We describe PFLE consultation, co-design, and partnership in various BHDB activities and projects. In all three examples, we discuss the factors contributing to successful PFLE engagement, share lessons learned, and highlight areas for growth and improvement. By sharing how the BHDB navigated and fostered PFLE engagement, we hope to motivate and inspire the health informatics community to collectively chart their paths in PFLE engagement to support advancements in digital health and artificial intelligence.
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Affiliation(s)
- Joanna Yu
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Health and Technology, Vector Institute for Artificial Intelligence, Toronto, ON, Canada
| | - Nelson Shen
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- AMS Healthcare, Toronto, ON, Canada
| | - Susan Conway
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Melissa Hiebert
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Benson Lai-Zhao
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Miriam McCann
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Rohan R. Mehta
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Morena Miranda
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Connie Putterman
- Centre for Addictions and Mental Health, Toronto, ON, Canada
- CanChild, Hamilton, ON, Canada
- CHILD-BRIGHT Network, Montreal, QC, Canada
- Kids Brain Health Network, Burnaby, ON, Canada
- Province of Ontario Neurodevelopmental (POND) Network, Toronto, ON, Canada
| | - Jose Arturo Santisteban
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Nicole Thomson
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Courtney Young
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | | | - Kimberly Hunter
- Centre for Addictions and Mental Health, Toronto, ON, Canada
| | - Sean Hill
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Health and Technology, Vector Institute for Artificial Intelligence, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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10
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Teodorowski P, Rodgers SE, Fleming K, Tahir N, Ahmed S, Frith L. Exploring how to improve the involvement of Polish and South Asian communities around big data research. A qualitative study using COM-B model. Int J Popul Data Sci 2023; 8:2130. [PMID: 37670958 PMCID: PMC10476635 DOI: 10.23889/ijpds.v8i1.2130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/07/2023] Open
Abstract
Introduction Involving public contributors helps researchers to ensure that public views are taken into consideration when designing and planning research, so that it is person-centred and relevant to the public. This paper will consider public involvement in big data research. Inclusion of different communities is needed to ensure everyone's voice is heard. However, there remains limited evidence on how to improve the involvement of seldom-heard communities in big data research. Objectives This study aims to understand how South Asians and Polish communities in the UK can be encouraged to participate in public involvement initiatives in big data research. Methods Forty interviews were conducted with Polish (n=20) and South Asian (n=20) participants on Zoom. The participants were living in the United Kingdom and had not previously been involved as public contributors. Transcribed interviews were analysed using reflexive thematic analysis. Results We identified eight themes. The 'happy to reuse data' theme sets the scene by exploring our participants' views towards big data research and under what circumstances they thought that data could be used. The remaining themes were mapped under the capability-opportunity-motivation-behaviour (COM-B) model, as developed by Michie and colleagues. This allowed us to discuss multiple factors that could influence people's willingness to become public contributors. Conclusions Our study is the first to explore how to improve the involvement and engagement of seldom-heard communities in big data research using the COM-B model. The results have the potential to support researchers who want to identify what can influence members of the public to be involved. By using the COM-B model, it is possible to determine what measures could be implemented to better engage these communities.
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Affiliation(s)
- Piotr Teodorowski
- Department of Public Health, Policy & Systems, University of Liverpool
| | - Sarah E. Rodgers
- Department of Public Health, Policy & Systems, University of Liverpool
| | - Kate Fleming
- National Disease Registration Service, NHS England
| | | | | | - Lucy Frith
- Centre for Social Ethics and Policy, University of Manchester
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11
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Landers C, Ormond KE, Blasimme A, Brall C, Vayena E. Talking Ethics Early in Health Data Public Private Partnerships. JOURNAL OF BUSINESS ETHICS : JBE 2023; 190:649-659. [PMID: 38487176 PMCID: PMC10933190 DOI: 10.1007/s10551-023-05425-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 04/25/2023] [Indexed: 03/17/2024]
Abstract
Data access and data sharing are vital to advance medicine. A growing number of public private partnerships are set up to facilitate data access and sharing, as private and public actors possess highly complementary health data sets and treatment development resources. However, the priorities and incentives of public and private organizations are frequently in conflict. This has complicated partnerships and sparked public concerns around ethical issues such as trust, justice or privacy-in turn raising an important problem in business and data ethics: how can ethical theory inform the practice of public and private partners to mitigate misaligned incentives, and ensure that they can deliver societally beneficial innovation? In this paper, we report on the development of the Swiss Personalized Health Network's ethical guidelines for health data sharing in public private partnerships. We describe the process of identifying ethical issues and engaging core stakeholders to incorporate their practical reality on these issues. Our report highlights core ethical issues in health data public private partnerships and provides strategies for how to overcome these in the Swiss health data context. By agreeing on and formalizing ethical principles and practices at the beginning of a partnership, partners and society can benefit from a relationship built around a mutual commitment to ethical principles. We present this summary in the hope that it will contribute to the global data sharing dialogue.
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Affiliation(s)
- Constantin Landers
- Health Ethics and Policy Lab, ETH Zurich, Hottingerstrasse 10, 8032 Zurich, Switzerland
| | - Kelly E. Ormond
- Health Ethics and Policy Lab, ETH Zurich, Hottingerstrasse 10, 8032 Zurich, Switzerland
| | - Alessandro Blasimme
- Health Ethics and Policy Lab, ETH Zurich, Hottingerstrasse 10, 8032 Zurich, Switzerland
| | - Caroline Brall
- Ethics and Policy Lab, Multidisciplinary Center for Infectious Diseases, University of Bern, Länggassstrasse 49a, 3012 Bern, Switzerland
- Institute of Philosophy, University of Bern, Länggassstrasse 49a, 3012 Bern, Switzerland
| | - Effy Vayena
- Health Ethics and Policy Lab, ETH Zurich, Hottingerstrasse 10, 8032 Zurich, Switzerland
- ELSI Advisory Group, Swiss Personalized Health Network, Laupenstrasse 7, 3001 Bern, Switzerland
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12
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Teodorowski P, Rodgers SE, Fleming K, Tahir N, Ahmed S, Frith L. 'To me, it's ones and zeros, but in reality that one is death': A qualitative study exploring researchers' experience of involving and engaging seldom-heard communities in big data research. Health Expect 2023; 26:882-891. [PMID: 36691930 PMCID: PMC10010102 DOI: 10.1111/hex.13713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 12/21/2022] [Accepted: 01/05/2023] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Big data research requires public support. It has been argued that this can be achieved by public involvement and engagement to ensure that public views are at the centre of research projects. Researchers should aim to include diverse communities, including seldom-heard voices, to ensure that a range of voices are heard and that research is meaningful to them. OBJECTIVE We explored how researchers involve and engage seldom-heard communities around big data research. METHODS This is a qualitative study. Researchers who had experience of involving or engaging seldom-heard communities in big data research were recruited. They were based in England (n = 5), Scotland (n = 4), Belgium (n = 2) and Canada (n = 1). Twelve semistructured interviews were conducted on Zoom. All interviews were audio-recorded and transcribed, and we used reflexive thematic analysis to analyse participants' experiences. RESULTS The analysis highlighted the complexity of involving and engaging seldom-heard communities around big data research. Four themes were developed to represent participants' experiences: (1) abstraction and complexity of big data, (2) one size does not fit all, (3) working in partnership and (4) empowering the public contribution. CONCLUSION The study offers researchers a better understanding of how to involve and engage seldom-heard communities in a meaningful way around big data research. There is no one right approach, with involvement and engagement activities required to be project-specific and dependent on the public contributors, researchers' needs, resources and time available. PATIENT AND PUBLIC INVOLVEMENT Two public contributors are authors of the paper and they were involved in the study design, analysis and writing.
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Affiliation(s)
- Piotr Teodorowski
- Department of Public Health, Policy & Systems, University of Liverpool, Liverpool, UK
| | - Sarah E Rodgers
- Department of Public Health, Policy & Systems, University of Liverpool, Liverpool, UK
| | - Kate Fleming
- National Disease Registration Service, NHS Digital, Liverpool, UK
| | | | | | - Lucy Frith
- Department of Law, University of Manchester, Manchester, UK
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13
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Kusunose M, Muto K. Public attitudes toward cloud computing and willingness to share personal health records (PHRs) and genome data for health care research in Japan. Hum Genome Var 2023; 10:11. [PMID: 36990988 PMCID: PMC10060394 DOI: 10.1038/s41439-023-00240-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 01/17/2023] [Accepted: 02/09/2023] [Indexed: 03/31/2023] Open
Abstract
Japan's government aims to promote the linkage of medical records, including medical genomic testing data and personal health records (PHRs), via cloud computing (the cloud). However, linking national medical records and using them for health care research can be controversial. Additionally, many ethical issues with using cloud networks with health care and genome data have been noted. However, no research has yet explored the Japanese public's opinions about their PHRs, including genome data, being shared for health care research or the use of the cloud for storing and analyzing such data. Therefore, we conducted a survey in March 2021 to clarify the public's attitudes toward sharing their PHRs, including genome data and using the cloud for health care research. We analyzed data to experimentally create digital health basic literacy scores (BLSs). Our results showed that the Japanese public had concerns about data sharing that overlapped with structural cloud computing issues. The effect of incentives on changes in participants' willingness to share data (WTSD) was limited. Instead, there could be a correlation between WTSD and BLSs. Finally, we argue that it is vital to consider not only researchers but also research participants as value cocreators in health care research conducted through the cloud to overcome both parties' vulnerability.
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Affiliation(s)
- Mayumi Kusunose
- The Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
- The Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan.
| | - Kaori Muto
- The Department of Public Policy, The Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
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Ford E, Rees-Roberts M, Stanley K, Goddard K, Giles S, Armes J, Ikhile D, Madzvamuse A, Spencer-Hughes V, George A, Farmer C, Cassell J. Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups. Int J Popul Data Sci 2023; 5:2114. [PMID: 37671318 PMCID: PMC10476239 DOI: 10.23889/ijpds.v5i3.2114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Introduction Digital programmes in the newly created NHS integrated care boards (ICBs) in the United Kingdom mean that curation and linkage of anonymised patient data is underway in many areas for the first time. In Kent, Surrey and Sussex (KSS), in Southeast England, public health teams want to use these datasets to answer strategic population health questions, but public expectations around use of patient data are unknown. Objectives We aimed to engage with citizens of KSS to gather their views and expectations of data linkage and re-use, through deliberative discussions. Methods We held five 3-hour deliberative focus groups with 79 citizens of KSS, presenting information about potential uses of data, safeguards, and mechanisms for public involvement in governance and decision making about datasets. After each presentation, participants discussed their views in facilitated small groups which were recorded, transcribed and analysed thematically. Results The focus groups generated 15 themes representing participants' views on the benefits, risks and values for safeguarding linked data. Participants largely supported use of patient data to improve health service efficiency and resource management, preventative services and out of hospital care, joined-up services and information flows. Most participants expressed concerns about data accuracy, breaches and hacking, and worried about commercial use of data. They suggested that transparency of data usage through audit trails and clear information about accountability, ensuring data re-use does not perpetuate stigma and discrimination, ongoing, inclusive and valued involvement of the public in dataset decision-making, and a commitment to building trust, would meet their expectations for responsible data use. Conclusions Participants were largely favourable about the proposed uses of patient linked datasets but expected a commitment to transparency and public involvement. Findings were mapped to previous tenets of social license and can be used to inform ICB digital programme teams on how to proceed with use of linked datasets in a trustworthy and socially acceptable way.
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Affiliation(s)
| | | | | | | | - Sarah Giles
- Digital Innovation Theme Public Advisor, NIHR ARC -KSS (Applied Research Collaboration Kent, Surrey, and Sussex)
| | - Jo Armes
- University of Surrey, Guildford, UK
| | | | - Anotida Madzvamuse
- University of Sussex, Brighton, UK
- University of British Columbia, Canada
| | | | | | - Chris Farmer
- Centre for Health Services Studies, University of Kent, Canterbury, Kent, UK
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15
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Muller SHA, van Thiel GJMW, Mostert M, van Delden JJM. Dynamic consent, communication and return of results in large-scale health data reuse: Survey of public preferences. Digit Health 2023; 9:20552076231190997. [PMID: 37599899 PMCID: PMC10434987 DOI: 10.1177/20552076231190997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 07/13/2023] [Indexed: 08/22/2023] Open
Abstract
Dynamic consent forms a comprehensive, tailored approach for interacting with research participants. We conducted a survey study to inquire how research participants evaluate the elements of consent, information provision, communication and return of results within dynamic consent in a hypothetical health data reuse scenario. We distributed a digital questionnaire among a purposive sample of patient panel members. Data were analysed using descriptive and nonparametric inferential statistics. Respondents favoured the potential to manage changing consent preferences over time. There was much agreement between people favouring closer and more specific control over data reuse approval and those in favour of broader approval, facilitated by an opt-out system or an independent data reuse committee. People want to receive more information about reuse, outcomes and return of results. Respondents supported an interactive model of research participation, welcoming regular, diverse and interactive forms of communication, like a digital communication platform. Approval for reuse and providing meaningful information, including meaningful return of results, are intricately related to facilitating better communication. Respondents favoured return of actionable research results. These findings emphasize the potential of dynamic consent for enabling participants to maintain control over how their data are being used for which purposes by whom. Allowing different options to shape a dynamic consent interface in health data reuse in a personalized manner is pivotal to accommodate plurality in a flexible though robust manner. Interaction via dynamic consent enables participants to tailor the elements of participation they deem relevant to their own preferences, engaging diverse perspectives, interests and preferences.
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Affiliation(s)
- Sam HA Muller
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ghislaine JMW van Thiel
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Menno Mostert
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Johannes JM van Delden
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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16
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Kotecha D, Asselbergs FW, Achenbach S, Anker SD, Atar D, Baigent C, Banerjee A, Beger B, Brobert G, Casadei B, Ceccarelli C, Cowie MR, Crea F, Cronin M, Denaxas S, Derix A, Fitzsimons D, Fredriksson M, Gale CP, Gkoutos GV, Goettsch W, Hemingway H, Ingvar M, Jonas A, Kazmierski R, Løgstrup S, Thomas Lumbers R, Lüscher TF, McGreavy P, Piña IL, Roessig L, Steinbeisser C, Sundgren M, Tyl B, van Thiel G, van Bochove K, Vardas PE, Villanueva T, Vrana M, Weber W, Weidinger F, Windecker S, Wood A, Grobbee DE. CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research. Eur Heart J 2022; 43:3578-3588. [PMID: 36208161 PMCID: PMC9452067 DOI: 10.1093/eurheartj/ehac426] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/21/2022] [Indexed: 11/29/2022] Open
Abstract
Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes.
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Affiliation(s)
- Dipak Kotecha
- Institute of Cardiovascular Sciences, University of Birmingham, Medical School, Birmingham, UK
- University Hospitals Birmingham NHS Foundation Trust and Health Data Research UK Midlands, Birmingham, UK
- Department of Cardiology, Division of Heart and Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division of Heart and Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - Stephan Achenbach
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Stefan D Anker
- Department of Cardiology and Berlin Institute of Health Centre for Regenerative Therapies, German Centre for Cardiovascular Research (DZHK) partner site Berlin; Charité Universitätsmedizin Berlin, Germany
| | - Dan Atar
- Department of Cardiology, Oslo University Hospital, Ulleval, Oslo, Norway
- University of Oslo, Institute of Clinical Medicine, Oslo, Norway
| | - Colin Baigent
- MRC Population Health Research Unit, Nuffield Department of Population Health, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
| | - Amitava Banerjee
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
- University College London Hospitals NHS Trust, London, UK
| | | | | | - Barbara Casadei
- Division of Cardiovascular Medicine, John Radcliffe Hospital, University of Oxford NIHR Oxford Biomedical Research Centre, Oxford, UK
| | | | - Martin R Cowie
- Royal Brompton Hospital, Division of Guy’s St Thomas’ NHS Foundation Trust, London, UK
- School of Cardiovascular Medicine Sciences, King’s College London, London, UK
| | - Filippo Crea
- Department of Cardiovascular and Pulmonary Sciences, Catholic University of the Sacred Heart, Rome, Italy
- European Heart Journal, Oxford University Press, University of Oxford, Oxford, UK
| | - Maureen Cronin
- Vifor Pharma, Glattbrugg, Switzerland and Ava AG, Zurich, Switzerland
| | - Spiros Denaxas
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
- Alan Turing Institute, London, UK
- British Heart Foundation Data Science Centre, London, UK
| | | | - Donna Fitzsimons
- School of Nursing and Midwifery, Queen’s University Belfast, Northern Ireland
| | - Martin Fredriksson
- Late Clinical Development, Cardiovascular, Renal and Metabolism (CVRM), Biopharmaceuticals RD, AstraZeneca, Gothenburg, Sweden
| | - Chris P Gale
- Leeds Institute of Cardiovascular and Metabolic Medicine and Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Georgios V Gkoutos
- University Hospitals Birmingham NHS Foundation Trust and Health Data Research UK Midlands, Birmingham, UK
- College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Wim Goettsch
- National Health Care Institute (ZIN), Diemen, Netherlands
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands
| | - Harry Hemingway
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
- Department of Neuroradiology, Karolinska University Hospital Stockholm, Stockholm, Sweden
| | - Adrian Jonas
- Data and Analytics Group, National Institute for Health and Care Excellence, London, UK
| | - Robert Kazmierski
- Office of Cardiovascular Devices, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - R Thomas Lumbers
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
- Barts Health NHS Trust and University College London Hospitals NHS Trust
| | - Thomas F Lüscher
- Centre for Molecular Cardiology, University of Zurich, Zurich, Switzerland
- Research, Education & Development, Royal Brompton and Harefield Hospitals, London, UK
- Faculty of Medicine, Imperial College London, London, UK
| | - Paul McGreavy
- European Society of Cardiology Patient Forum, European Society of Cardiology, Brussels, Belgium
| | - Ileana L Piña
- Central Michigan University College of Medicine, Midlands, MI, USA
- Centre for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - Carl Steinbeisser
- Bayer AG, Leverkusen, Germany
- Steinbeisser Project Management, Munich, Germany
| | - Mats Sundgren
- Data Science AI, Biopharmaceuticals RD, AstraZeneca, Gothenburg, Sweden
| | - Benoît Tyl
- Centre for Therapeutic Innovation, Cardiovascular and Metabolic Disease, Institut de Recherches Internationales Servier, Suresnes, France
| | - Ghislaine van Thiel
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, Netherlands
| | | | - Panos E Vardas
- Hygeia, Mitera, Hospitals Hellenic Health Group, Athens, Greece
- European Heart Agency, European Society of Cardiology, Brussels, Belgium
| | | | | | | | | | - Stephan Windecker
- Department of Cardiology, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Angela Wood
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Diederick E Grobbee
- Department of Epidemiology, University Medical Centre Utrecht, Division Julius Centrum, Utrecht, Netherlands
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17
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Kotecha D, Asselbergs FW, Achenbach S, Anker SD, Atar D, Baigent C, Banerjee A, Beger B, Brobert G, Casadei B, Ceccarelli C, Cowie MR, Crea F, Cronin M, Denaxas S, Derix A, Fitzsimons D, Fredriksson M, Gale CP, Gkoutos GV, Goettsch W, Hemingway H, Ingvar M, Jonas A, Kazmierski R, Løgstrup S, Lumbers RT, Lüscher TF, McGreavy P, Piña IL, Roessig L, Steinbeisser C, Sundgren M, Tyl B, Thiel GV, Bochove KV, Vardas PE, Villanueva T, Vrana M, Weber W, Weidinger F, Windecker S, Wood A, Grobbee DE. CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research. Lancet Digit Health 2022; 4:e757-e764. [PMID: 36050271 DOI: 10.1016/s2589-7500(22)00151-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 07/20/2022] [Indexed: 11/16/2022]
Abstract
Big data is important to new developments in global clinical science that aim to improve the lives of patients. Technological advances have led to the regular use of structured electronic health-care records with the potential to address key deficits in clinical evidence that could improve patient care. The COVID-19 pandemic has shown this potential in big data and related analytics but has also revealed important limitations. Data verification, data validation, data privacy, and a mandate from the public to conduct research are important challenges to effective use of routine health-care data. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including representation from patients, clinicians, scientists, regulators, journal editors, and industry members. In this Review, we propose the CODE-EHR minimum standards framework to be used by researchers and clinicians to improve the design of studies and enhance transparency of study methods. The CODE-EHR framework aims to develop robust and effective utilisation of health-care data for research purposes.
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Affiliation(s)
- Dipak Kotecha
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Department of Cardiology, Division of Heart and Lungs, University of Utrecht, Utrecht, Netherlands.
| | - Folkert W Asselbergs
- Health Data Research UK London, London, UK; Institute of Cardiovascular Science and Institute of Health Informatics, Faculty of Population Health Sciences, University College London, London, UK
| | - Stephan Achenbach
- Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Stefan D Anker
- Department of Cardiology and Berlin Institute of Health Centre for Regenerative Therapies, German Centre for Cardiovascular Research, Charité Universitätsmedizin, Berlin, Germany
| | - Dan Atar
- Department of Cardiology, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Colin Baigent
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
| | - Amitava Banerjee
- Health Data Research UK London, London, UK; University College London Hospitals NHS Trust, London, UK
| | | | | | - Barbara Casadei
- Division of Cardiovascular Medicine, John Radcliffe Hospital, University of Oxford National Institute for Health and Care Research Oxford Biomedical Research Centre, Oxford, UK
| | | | - Martin R Cowie
- Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK; School of Cardiovascular Medicine Sciences, King's College London, London, UK
| | - Filippo Crea
- European Heart Journal, Oxford University Press, University of Oxford, Oxford, UK; Department of Cardiovascular and Pulmonary Sciences, Catholic University of the Sacred Heart, Rome, Italy
| | - Maureen Cronin
- Vifor Pharma, Glattbrugg, Switzerland; Ava, Zurich, Switzerland
| | - Spiros Denaxas
- Health Data Research UK London, London, UK; Alan Turing Institute, London, UK; British Heart Foundation Data Science Centre, London, UK
| | | | - Donna Fitzsimons
- School of Nursing and Midwifery, Queen's University Belfast, Northern Ireland
| | - Martin Fredriksson
- Late Clinical Development, Cardiovascular, Renal and Metabolism, Biopharmaceuticals, AstraZeneca, Gothenburg, Sweden
| | - Chris P Gale
- Leeds Institute of Cardiovascular and Metabolic Medicine and Leeds Institute for Data Analytics, University of Leeds, Leeds, UK; Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Georgios V Gkoutos
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Wim Goettsch
- University Medical Centre Utrecht, and Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, Netherlands; National Health Care Institute, Diemen, Netherlands
| | | | - Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden; Department of Neuroradiology, Karolinska University Hospital Stockholm, Stockholm, Sweden
| | - Adrian Jonas
- Data and Analytics Group, National Institute for Health and Care Excellence, London, UK
| | - Robert Kazmierski
- Office of Cardiovascular Devices, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - R Thomas Lumbers
- Health Data Research UK London, London, UK; Institute of Health Informatics, Barts Health NHS Trust and University College London Hospitals NHS Trust, London, UK
| | - Thomas F Lüscher
- Centre for Molecular Cardiology, University of Zurich, Zurich, Switzerland; Research, Education and Development, Royal Brompton and Harefield Hospitals, London, UK; Faculty of Medicine, Imperial College London, London, UK
| | - Paul McGreavy
- European Society of Cardiology Patient Forum, European Society of Cardiology, Brussels, Belgium
| | - Ileana L Piña
- Centre for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA; College of Medicine, Central Michigan University, Midlands MI, USA
| | | | - Carl Steinbeisser
- Bayer, Leverkusen, Germany; Steinbeisser Project Management, Munich, Germany
| | - Mats Sundgren
- Data Science and Artificial Intelligence, Biopharmaceuticals, AstraZeneca, Gothenburg, Sweden
| | - Benoît Tyl
- Centre for Therapeutic Innovation, Cardiovascular and Metabolic Disease, Institut de Recherches Internationales Servier, Suresnes, France
| | - Ghislaine van Thiel
- Julius Center for Health Sciences and Primary Care, University of Utrecht, Utrecht, Netherlands
| | | | - Panos E Vardas
- Hygeia, Mitera, Hospitals Hellenic Health Group, Athens, Greece; European Heart Agency, European Society of Cardiology, Brussels, Belgium
| | | | | | - Wim Weber
- The British Medical Journal, London, UK
| | | | - Stephan Windecker
- Department of Cardiology, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Angela Wood
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Muller SHA, van Thiel GJMW, Vrana M, Mostert M, van Delden JJM. Patients' and Publics' Preferences for Data-Intensive Health Research Governance: Survey Study. JMIR Hum Factors 2022; 9:e36797. [PMID: 36069794 PMCID: PMC9494211 DOI: 10.2196/36797] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 05/18/2022] [Accepted: 07/18/2022] [Indexed: 11/28/2022] Open
Abstract
Background Patients and publics are generally positive about data-intensive health research. However, conditions need to be fulfilled for their support. Ensuring confidentiality, security, and privacy of patients’ health data is pivotal. Patients and publics 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. Yet, the potential of public benefit highlights the potential of building trust to attenuate these perceptions of harm and risk. Nevertheless, empirical evidence on how conditions for support of data-intensive health research can be operationalized to that end remains scant. Objective 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. Methods We distributed a digital questionnaire among a purposive sample of patients and publics. Data were analyzed using descriptive statistics and nonparametric inferential statistics to compare group differences and explore associations between policy preferences. Results Study participants (N=987) strongly favored sharing their health data for scientific health research. Personal decision-making about which research projects health data are shared with (346/980, 35.3%), which researchers/organizations can have access (380/978, 38.9%), and the provision of information (458/981, 46.7%) were found highly important. Health data–sharing policies strengthening direct personal control, like being able to decide under which conditions health data are shared (538/969, 55.5%), were found highly important. Policies strengthening collective governance, like reliability checks (805/967, 83.2%) and security safeguards (787/976, 80.6%), were also found highly important. Further analysis revealed that participants willing to share health data, to a lesser extent, demanded policies strengthening direct personal control than participants who were reluctant to share health data. This was the case for the option to have health data deleted at any time (P<.001) and the ability to decide the conditions under which health data can be shared (P<.001). Overall, policies and measures enforcing conditions for support at the collective level of governance, like having an independent committee to evaluate requests for access to health data (P=.02), were most strongly favored. This also applied to participants who explicitly stressed that it was important to be able to decide the conditions under which health data can be shared, for instance, whether sanctions on data misuse are in place (P=.03). Conclusions This study revealed that both a positive attitude toward health data sharing and demand for personal decision-making abilities were associated with policies and measures strengthening control at the collective level of governance. We recommend pursuing the development of this type of governance policy. More importantly, further study is required to understand how governance policies and measures can contribute to the trustworthiness of data-intensive health research.
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Affiliation(s)
- Sam H A Muller
- Department of Medical Humanities, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Ghislaine J M W van Thiel
- Department of Medical Humanities, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | | | - Menno Mostert
- Department of Medical Humanities, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Johannes J M van Delden
- Department of Medical Humanities, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
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19
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Kotecha D, Asselbergs FW, Achenbach S, Anker SD, Atar D, Baigent C, Banerjee A, Beger B, Brobert G, Casadei B, Ceccarelli C, Cowie MR, Crea F, Cronin M, Denaxas S, Derix A, Fitzsimons D, Fredriksson M, Gale CP, Gkoutos GV, Goettsch W, Hemingway H, Ingvar M, Jonas A, Kazmierski R, Løgstrup S, Lumbers RT, Lüscher TF, McGreavy P, Piña IL, Roessig L, Steinbeisser C, Sundgren M, Tyl B, van Thiel G, van Bochove K, Vardas PE, Villanueva T, Vrana M, Weber W, Weidinger F, Windecker S, Wood A, Grobbee DE. CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research. BMJ 2022; 378:e069048. [PMID: 36562446 PMCID: PMC9403753 DOI: 10.1136/bmj-2021-069048] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/21/2022] [Indexed: 12/27/2022]
Affiliation(s)
- Dipak Kotecha
- Institute of Cardiovascular Sciences, University of Birmingham, Medical School, Birmingham, UK
- Department of Cardiology, Division of Heart and Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division of Heart and Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - Stephan Achenbach
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Stefan D Anker
- Department of Cardiology and Berlin Institute of Health Centre for Regenerative Therapies, German Centre for Cardiovascular Research (DZHK) partner site Berlin; Charité Universitätsmedizin Berlin, Germany
| | - Dan Atar
- Department of Cardiology, Oslo University Hospital, Ulleval, Oslo, Norway
- University of Oslo, Institute of Clinical Medicine, Oslo, Norway
| | - Colin Baigent
- MRC Population Health Research Unit, Nuffield Department of Population Health, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
| | - Amitava Banerjee
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
- University College London Hospitals NHS Trust, London, UK
| | | | | | - Barbara Casadei
- Division of Cardiovascular Medicine, John Radcliffe Hospital, University of Oxford NIHR Oxford Biomedical Research Centre, Oxford, UK
| | | | - Martin R Cowie
- Royal Brompton Hospital, Division of Guy's St Thomas' NHS Foundation Trust, London, UK
- School of Cardiovascular Medicine Sciences, King's College London, London, UK
| | - Filippo Crea
- Department of Cardiovascular and Pulmonary Sciences, Catholic University of the Sacred Heart, Rome, Italy
- European Heart Journal, Oxford University Press, University of Oxford, Oxford, UK
| | - Maureen Cronin
- Vifor Pharma, Glattbrugg, Switzerland and Ava AG, Zurich, Switzerland
| | - Spiros Denaxas
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
- Alan Turing Institute, London, UK
- British Heart Foundation Data Science Centre, London, UK
| | | | - Donna Fitzsimons
- School of Nursing and Midwifery, Queen's University Belfast, Northern Ireland
| | - Martin Fredriksson
- Late Clinical Development, Cardiovascular, Renal and Metabolism (CVRM), Biopharmaceuticals RD, AstraZeneca, Gothenburg, Sweden
| | - Chris P Gale
- Leeds Institute of Cardiovascular and Metabolic Medicine and Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Georgios V Gkoutos
- University Hospitals Birmingham NHS Foundation Trust and Health Data Research UK Midlands, Birmingham, UK
- College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Wim Goettsch
- National Health Care Institute (ZIN), Diemen, Netherlands
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands
| | - Harry Hemingway
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
- Department of Neuroradiology, Karolinska University Hospital Stockholm, Stockholm, Sweden
| | - Adrian Jonas
- Data and Analytics Group, National Institute for Health and Care Excellence, London, UK
| | - Robert Kazmierski
- Office of Cardiovascular Devices, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - R Thomas Lumbers
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
- Barts Health NHS Trust and University College London Hospitals NHS Trust
| | - Thomas F Lüscher
- Centre for Molecular Cardiology, University of Zurich, Zurich, Switzerland
- Faculty of Medicine, Imperial College London, London, UK
| | - Paul McGreavy
- European Society of Cardiology Patient Forum, European Society of Cardiology, Brussels, Belgium
| | - Ileana L Piña
- Central Michigan University College of Medicine, Midlands, MI, USA
- Centre for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - Carl Steinbeisser
- Bayer AG, Leverkusen, Germany
- Steinbeisser Project Management, Munich, Germany
| | - Mats Sundgren
- Data Science AI, Biopharmaceuticals RD, AstraZeneca, Gothenburg, Sweden
| | - Benoît Tyl
- Centre for Therapeutic Innovation, Cardiovascular and Metabolic Disease, Institut de Recherches Internationales Servier, Suresnes, France
| | - Ghislaine van Thiel
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, Netherlands
| | | | - Panos E Vardas
- Hygeia, Mitera, Hospitals Hellenic Health Group, Athens, Greece
- European Heart Agency, European Society of Cardiology, Brussels, Belgium
| | | | | | | | | | - Stephan Windecker
- Department of Cardiology, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Angela Wood
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Diederick E Grobbee
- Department of Epidemiology, University Medical Centre Utrecht, Division Julius Centrum, Utrecht, Netherlands
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20
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Bockhold S, McNulty J, Abdurakman E, Bezzina P, Drey N, England A, Flinton D, Khine R, McEntee M, Mekiš N, Precht H, Rainford L, Sá Dos Reis C, Santos A, Syrgiamiotis V, Willis S, Woodley J, Beardmore C, Harris R, O'Regan T, Malamateniou C. Research ethics systems, processes, and awareness across Europe: Radiography research ethics standards for Europe (RRESFE). Radiography (Lond) 2022; 28:1032-1041. [PMID: 35964488 DOI: 10.1016/j.radi.2022.07.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/29/2022] [Accepted: 07/02/2022] [Indexed: 10/31/2022]
Abstract
INTRODUCTION The Radiography Research Ethics Standards for Europe (RRESFE) project aims to provide a cross-sectional snapshot of current research ethics systems, processes, and awareness of such, across Europe together with identifying the associated challenges, education, and training needs. METHODS A cross-sectional online survey targeting radiography researchers in Europe was conducted. Data collection took place between April 26 and July 12, 2021, using a snowball sampling approach. Descriptive and analytical statistics were used to identify trends in research ethics frameworks across Europe. RESULTS 285 responses were received across 33 European and 23 non-European countries. Most (n = 221; 95%) European respondents stated ethics approval is required before commencing research in their country. Requirements around research ethics approval and awareness of such requirements varied by European region (X2 (2, n = 129) = 7.234, p = 0.013) and were found to differ depending on the type of research participant and study design. Additionally, European respondents reported ethics approval is a national requirement more often than their non-European counterparts (X2 (1, n = 282) = 4.316, p = 0.049). Requirements for ethics approval were also associated with the undergraduate programme duration (2-year vs. 3-year vs. 3.5 year vs. 4-year vs. multiple programme durations; X2 (4, n = 231) = 10.075, p = 0.016) and availability of postgraduate training (postgraduate training available vs. postgraduate training not available; X2 (1, n = 231) = 15.448, p = <0.001) within respondents' country. CONCLUSION Respondents from countries with longer programme durations/availability of multiple programme lengths, availability of postgraduate training, and establishment of European Qualifications Framework Level 6 were generally associated with less uncertainty and more comprehensive research ethics requirements. IMPLICATIONS FOR PRACTICE Results are informative of the current status of research ethics within evidence-based radiography.
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Affiliation(s)
- S Bockhold
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Ireland.
| | - J McNulty
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Ireland.
| | - E Abdurakman
- Division of Midwifery and Radiography, School of Health Sciences, City University of London, United Kingdom
| | - P Bezzina
- Radiography, Faculty of Health Sciences, L-Università ta' Malta, Malta
| | - N Drey
- Division of Nursing, School of Health Sciences, City University of London, United Kingdom
| | - A England
- Discipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Ireland
| | - D Flinton
- Division of Midwifery and Radiography, School of Health Sciences, City University of London, United Kingdom
| | - R Khine
- School of Health Care and Social Work, Buckinghamshire New University, United Kingdom
| | - M McEntee
- Discipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Ireland
| | - N Mekiš
- Medical Imaging and Radiotherapy, Faculty of Health Sciences, University of Ljubljana, Slovenia
| | - H Precht
- Diagnostic and Treatment and Radiography Education, Health Sciences Research Centre, UCL University College, Denmark
| | - L Rainford
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Ireland
| | - C Sá Dos Reis
- Radiological Medical Imaging Technology, School of Health Sciences, University of Applied Sciences and Arts Western Switzerland, Lausanne, Switzerland
| | - A Santos
- Medical Imaging and Radiotherapy, ESTESC-Coimbra Health School, Instituto Politécnico de Coimbra, Portugal
| | - V Syrgiamiotis
- CT-MRI Department, General Children's Hospital of Athens Agia Sophia, and University of West Attica, Greece
| | - S Willis
- Health Education England, National Health Service, London, United Kingdom
| | - J Woodley
- School of Health and Social Wellbeing, Faculty of Health and Applied Sciences, University of the West of England, Bristol, United Kingdom
| | - C Beardmore
- Society and College of Radiographers, London, United Kingdom
| | - R Harris
- Society and College of Radiographers, London, United Kingdom
| | - T O'Regan
- Society and College of Radiographers, London, United Kingdom
| | - C Malamateniou
- Division of Midwifery and Radiography, School of Health Sciences, City University of London, United Kingdom.
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21
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Okun S, Hanger M, Browne-James L, Montgomery T, Rafaloff G, van Delden JJ. Commitments for Ethically Responsible Sourcing, Use, and Reuse of Patient Data in the Digital Age: Co-Creation Process (Preprint). J Med Internet Res 2022; 25:e41095. [PMID: 37145833 DOI: 10.2196/41095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 11/26/2022] [Accepted: 03/16/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND Personal information, including health-related data, may be used in ways we did not intend when it was originally shared. However, the organizations that collect these data do not always have the necessary social license to use and share it. Although some technology companies have published principles on the ethical use of artificial intelligence, the foundational issue of what is and is not acceptable to do with data, not just the analytical tools to manage it, has not been fully considered. Furthermore, it is unclear whether input from the public or patients has been included. In 2017, the leadership at a web-based patient research network began to envision a new kind of community compact that laid out what the company believed, how the company should behave, and what it promised both to the individuals who engaged with them and to the community at large. While having already earned a social license from patient members as a trusted data steward with strong privacy, transparency, and openness policies, the company sought to protect and strengthen that social license by creating a socially and ethically responsible data contract. Going beyond regulatory and legislative requirements, this contract considered the ethical use of multiomics and phenotypic data in addition to patient-reported and generated data. OBJECTIVE A multistakeholder working group sought to develop easy-to-understand commitments that established expectations for data stewardship, governance, and accountability from those who seek to collect, use, and share personal data. The working group cocreated a framework that was radically patient-first in its thinking and collaborative in the process of its codevelopment; it reflected the values, ideas, opinions, and perspectives of the cocreators, inclusive of patients and the public. METHODS Leveraging the conceptual frameworks of cocreation and participatory action research, a mixed methods approach was used that included a landscape analysis, listening sessions, and a 12-question survey. The methodological approaches used by the working group were guided by the combined principles of biomedical ethics and social license and shaped through a collaborative and reflective process with similarities to reflective equilibrium, a method well known in ethics. RESULTS Commitments for the Digital Age are the output of this work. The six commitments in order of priority are (1) continuous and shared learning; (2) respect and empower individual choice; (3) informed and understood consent; (4) people-first governance; (5) open communication and accountable conduct; and (6) inclusivity, diversity, and equity. CONCLUSIONS These 6 commitments-and the development process itself-have broad applicability as models for (1) other organizations that rely on digitized data sources from individuals and (2) patients who seek to strengthen operational policies for the ethical and responsible collection, use, and reuse of that data.
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Affiliation(s)
- Sally Okun
- Clinical Trials Transformation Initiative, Durham, NC, United States
| | - Morgan Hanger
- Clinical Trials Transformation Initiative, Durham, NC, United States
| | | | | | - Gary Rafaloff
- Meridian Investment Partners LLC, Westlake, FL, United States
| | - Johannes Jm van Delden
- Department of Medical Humanities, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
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22
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Köngeter A, Schickhardt C, Jungkunz M, Bergbold S, Mehlis K, Winkler EC. Patients’ willingness to provide their clinical data for research purposes and acceptance of different consent models: Findings from a representative survey of cancer patients in Germany (Preprint). J Med Internet Res 2022; 24:e37665. [PMID: 36006690 PMCID: PMC9459939 DOI: 10.2196/37665] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/27/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Anja Köngeter
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Christoph Schickhardt
- Section for Translational Medical Ethics, National Center for Tumor Diseases, German Cancer Research Center, Heidelberg, Germany
| | - Martin Jungkunz
- Section for Translational Medical Ethics, National Center for Tumor Diseases, German Cancer Research Center, Heidelberg, Germany
| | - Susanne Bergbold
- Epidemiological Cancer Registry Baden-Württemberg, German Cancer Research Center, Heidelberg, Germany
| | - Katja Mehlis
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Eva C Winkler
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
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23
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The Social Data Foundation model: Facilitating health and social care transformation through datatrust services. DATA & POLICY 2022. [DOI: 10.1017/dap.2022.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Abstract
Turning the wealth of health and social data into insights to promote better public health, while enabling more effective personalized care, is critically important for society. In particular, social determinants of health have a significant impact on individual health, well-being, and inequalities in health. However, concerns around accessing and processing such sensitive data, and linking different datasets, involve significant challenges, not least to demonstrate trustworthiness to all stakeholders. Emerging datatrust services provide an opportunity to address key barriers to health and social care data linkage schemes, specifically a loss of control experienced by data providers, including the difficulty to maintain a remote reidentification risk over time, and the challenge of establishing and maintaining a social license. Datatrust services are a sociotechnical evolution that advances databases and data management systems, and brings together stakeholder-sensitive data governance mechanisms with data services to create a trusted research environment. In this article, we explore the requirements for datatrust services, a proposed implementation—the Social Data Foundation, and an illustrative test case. Moving forward, such an approach would help incentivize, accelerate, and join up the sharing of regulated data, and the use of generated outputs safely amongst stakeholders, including healthcare providers, social care providers, researchers, public health authorities, and citizens.
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