1
|
Carey EG, Adeyemi FO, Neelakantan L, Fernandes B, Fazel M, Ford T, Burn AM. Preferences on Governance Models for Mental Health Data: Qualitative Study With Young People. JMIR Form Res 2024; 8:e50368. [PMID: 38652525 PMCID: PMC11077411 DOI: 10.2196/50368] [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: 06/30/2023] [Revised: 11/08/2023] [Accepted: 03/22/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Improving access to mental health data to accelerate research and improve mental health outcomes is a potentially achievable goal given the substantial data that can now be collected from mobile devices. Smartphones can provide a useful mechanism for collecting mental health data from young people, especially as their use is relatively ubiquitous in high-resource settings such as the United Kingdom and they have a high capacity to collect active and passive data. This raises the interesting opportunity to establish a large bank of mental health data from young people that could be accessed by researchers worldwide, but it is important to clarify how to ensure that this is done in an appropriate manner aligned with the values of young people. OBJECTIVE In this study, we discussed the preferences of young people in the United Kingdom regarding the governance, sharing, and use of their mental health data with the establishment of a global data bank in mind. We aimed to determine whether young people want and feel safe to share their mental health data; if so, with whom; and their preferences in doing so. METHODS Young people (N=46) were provided with 2 modules of educational material about data governance models and background in scientific research. We then conducted 2-hour web-based group sessions using a deliberative democracy methodology to reach a consensus where possible. Findings were analyzed using the framework method. RESULTS Young people were generally enthusiastic about contributing data to mental health research. They believed that broader availability of mental health data could be used to discover what improves or worsens mental health and develop new services to support young people. However, this enthusiasm came with many concerns and caveats, including distributed control of access to ensure appropriate use, distributed power, and data management that included diverse representation and sufficient ethical training for applicants and data managers. CONCLUSIONS Although it is feasible to use smartphones to collect mental health data from young people in the United Kingdom, it is essential to carefully consider the parameters of such a data bank. Addressing and embedding young people's preferences, including the need for robust procedures regarding how their data are managed, stored, and accessed, will set a solid foundation for establishing any global data bank.
Collapse
Affiliation(s)
- Emma Grace Carey
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | | | - Lakshmi Neelakantan
- School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Blossom Fernandes
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Mina Fazel
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Tamsin Ford
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Anne-Marie Burn
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
2
|
Etchegary H, Darmonkov G, Simmonds C, Pullman D, Rahman P. Public attitudes towards genomic data sharing: results from a provincial online survey in Canada. BMC Med Ethics 2023; 24:81. [PMID: 37805493 PMCID: PMC10560413 DOI: 10.1186/s12910-023-00967-0] [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: 01/23/2023] [Accepted: 10/04/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND While genomic data sharing can facilitate important health research and discovery benefits, these must be balanced against potential privacy risks and harms to individuals. Understanding public attitudes and perspectives on data sharing is important given these potential risks and to inform genomic research and policy that aligns with public preferences and needs. METHODS A cross sectional online survey measured attitudes towards genomic data sharing among members of the general public in an Eastern Canadian province. RESULTS Results showed a moderate comfort level with sharing genomic data, usually into restricted scientific databases with controlled access. Much lower comfort levels were observed for sharing data into open or publicly accessible databases. While respondents largely approved of sharing genomic data for health research permitted by a research ethics board, many general public members were concerned with who would have access to their data, with higher rates of approval for access from clinical or academic actors, but much more limited approval of access from commercial entities or governments. Prior knowledge about sequencing and about research ethics boards were both related to data sharing attitudes. CONCLUSIONS With evolving regulations and guidelines for genomics research and data sharing, it is important to consider the perspectives of participants most impacted by these changes. Participant information materials and informed consent documents must be explicit about the safeguards in place to protect genomic data and the policies governing the sharing of data. Increased public awareness of the role of research ethics boards and of the need for genomic data sharing more broadly is also needed.
Collapse
Affiliation(s)
- Holly Etchegary
- Faculty of Medicine, Memorial University, St. John's, NL, A1B 3V6, Canada.
| | - Georgia Darmonkov
- Faculty of Medicine, Memorial University, St. John's, NL, A1B 3V6, Canada
| | - Charlene Simmonds
- Research Initiatives and Services, Memorial University, St. John's, NL, A1B 3V6, Canada
| | - Daryl Pullman
- Faculty of Medicine, Memorial University, St. John's, NL, A1B 3V6, Canada
| | - Proton Rahman
- Faculty of Medicine, Memorial University, St. John's, NL, A1B 3V6, Canada
- Eastern Regional Health Authority, Memorial University and Rheumatologist, St. John's, NL, A1B 3V6, Canada
| |
Collapse
|
3
|
Martin D, Basodi S, Panta S, Rootes-Murdy K, Prae P, Sarwate AD, Kelly R, Romero J, Baker BT, Gazula H, Bockholt J, Turner JA, Esper NB, Franco AR, Plis S, Calhoun VD. Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. Front Neuroinform 2023; 17:1207721. [PMID: 37404336 PMCID: PMC10315678 DOI: 10.3389/fninf.2023.1207721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/02/2023] [Indexed: 07/06/2023] Open
Abstract
Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.
Collapse
Affiliation(s)
- Dylan Martin
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Sunitha Basodi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Sandeep Panta
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Paul Prae
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Anand D. Sarwate
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
- Department of Electrical and Computer Engineering, Rutgers University–New Brunswick, Piscataway, NJ, United States
| | - Ross Kelly
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Javier Romero
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Bradley T. Baker
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Harshvardhan Gazula
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Jeremy Bockholt
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Jessica A. Turner
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Nathalia B. Esper
- Center for the Developing Brain, Child Mind Institute, New York, NY, United States
| | - Alexandre R. Franco
- Center for the Developing Brain, Child Mind Institute, New York, NY, United States
- Center for Brain Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, United States
| | - Sergey Plis
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| |
Collapse
|
4
|
Martin D, Basodi S, Panta S, Rootes-Murdy K, Prae P, Sarwate AD, Kelly R, Romero J, Baker BT, Gazula H, Bockholt J, Turner J, Esper NB, Franco AR, Plis S, Calhoun VD. Enhancing Collaborative Neuroimaging Research: Introducing COINSTAC Vaults for Federated Analysis and Reproducibility. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.08.539852. [PMID: 37214791 PMCID: PMC10197552 DOI: 10.1101/2023.05.08.539852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.
Collapse
|
5
|
Bennett DA, Du H. An Overview of Methods and Exemplars of the Use of Mendelian Randomisation in Nutritional Research. Nutrients 2022; 14:3408. [PMID: 36014914 PMCID: PMC9412324 DOI: 10.3390/nu14163408] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/12/2022] [Accepted: 08/15/2022] [Indexed: 12/09/2022] Open
Abstract
Objectives: It is crucial to elucidate the causal relevance of nutritional exposures (such as dietary patterns, food intake, macronutrients intake, circulating micronutrients), or biomarkers in non-communicable diseases (NCDs) in order to find effective strategies for NCD prevention. Classical observational studies have found evidence of associations between nutritional exposures and NCD development, but such studies are prone to confounding and other biases. This has direct relevance for translation research, as using unreliable evidence can lead to the failure of trials of nutritional interventions. Facilitated by the availability of large-scale genetic data, Mendelian randomization studies are increasingly used to ascertain the causal relevance of nutritional exposures and biomarkers for many NCDs. Methods: A narrative overview was conducted in order to demonstrate and describe the utility of Mendelian randomization studies, for individuals with little prior knowledge engaged in nutritional epidemiological research. Results: We provide an overview, rationale and basic description of the methods, as well as strengths and limitations of Mendelian randomization studies. We give selected examples from the contemporary nutritional literature where Mendelian randomization has provided useful evidence on the potential causal relevance of nutritional exposures. Conclusions: The selected exemplars demonstrate the importance of well-conducted Mendelian randomization studies as a robust tool to prioritize nutritional exposures for further investigation.
Collapse
Affiliation(s)
- Derrick A. Bennett
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX1 3QR, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX1 3QR, UK
| |
Collapse
|
6
|
NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. Neuroinformatics 2022; 20:91-108. [PMID: 33948898 PMCID: PMC8566325 DOI: 10.1007/s12021-021-09525-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2021] [Indexed: 01/05/2023]
Abstract
The field of neuroimaging can greatly benefit from building machine learning models to detect and predict diseases, and discover novel biomarkers, but much of the data collected at various organizations and research centers is unable to be shared due to privacy or regulatory concerns (especially for clinical data or rare disorders). In addition, aggregating data across multiple large studies results in a huge amount of duplicated technical debt and the resources required can be challenging or impossible for an individual site to build. Training on the data distributed across organizations can result in models that generalize much better than models trained on data from any of organizations alone. While there are approaches for decentralized sharing, these often do not provide the highest possible guarantees of sample privacy that only cryptography can provide. In addition, such approaches are often focused on probabilistic solutions. In this paper, we propose an approach that leverages the potential of datasets spread among a number of data collecting organizations by performing joint analyses in a secure and deterministic manner when only encrypted data is shared and manipulated. The approach is based on secure multiparty computation which refers to cryptographic protocols that enable distributed computation of a function over distributed inputs without revealing additional information about the inputs. It enables multiple organizations to train machine learning models on their joint data and apply the trained models to encrypted data without revealing their sensitive data to the other parties. In our proposed approach, organizations (or sites) securely collaborate to build a machine learning model as it would have been trained on the aggregated data of all the organizations combined. Importantly, the approach does not require a trusted party (i.e. aggregator), each contributing site plays an equal role in the process, and no site can learn individual data of any other site. We demonstrate effectiveness of the proposed approach, in a range of empirical evaluations using different machine learning algorithms including logistic regression and convolutional neural network models on human structural and functional magnetic resonance imaging datasets.
Collapse
|
7
|
Igumbor JO, Bosire EN, Vicente-Crespo M, Igumbor EU, Olalekan UA, Chirwa TF, Kinyanjui SM, Kyobutungi C, Fonn S. Considerations for an integrated population health databank in Africa: lessons from global best practices. Wellcome Open Res 2021; 6:214. [PMID: 35224211 PMCID: PMC8844538 DOI: 10.12688/wellcomeopenres.17000.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2021] [Indexed: 12/17/2022] Open
Abstract
Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing. We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.
Collapse
Affiliation(s)
- Jude O. Igumbor
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| | - Edna N. Bosire
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| | - Marta Vicente-Crespo
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
- African Population and Health Research Centre, Nairobi, Kenya
| | - Ehimario U. Igumbor
- Nigeria Centre for Disease Control, Abuja, Nigeria
- School of Public Health, University of the Western Cape, Cape Town, Western Cape, South Africa
| | - Uthman A. Olalekan
- Warwick-Centre for Applied Health Research and Delivery (WCAHRD), Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Tobias F. Chirwa
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| | | | | | - Sharon Fonn
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| |
Collapse
|
8
|
Scheibner J, Sleigh J, Ienca M, Vayena E. Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review. J Am Med Inform Assoc 2021; 28:2039-2049. [PMID: 34151990 DOI: 10.1093/jamia/ocab096] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/27/2021] [Accepted: 05/21/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE Our scoping review aims to assess what legal, ethical, and socio-technical factors contribute to or inhibit the success of national eHealth system implementations. In addition, our review seeks to describe the characteristics and benefits of eHealth systems. MATERIALS AND METHODS We conducted a scoping review of literature published in English between January 2000 and 2020 using a keyword search on 5 databases: PubMed, Scopus, Web of Science, IEEEXplore, and ProQuest. After removal of duplicates, abstract screening, and full-text filtering, 86 articles were included from 8276 search results. RESULTS We identified 17 stakeholder groups, 6 eHealth Systems areas, and 15 types of legal regimes and standards. In-depth textual analysis revealed challenges mainly in implementation, followed by ethico-legal and data-related aspects. Key factors influencing success include promoting trust of the system, ensuring wider acceptance among users, reconciling the system with legal requirements, and ensuring an adaptable technical platform. DISCUSSION Results revealed support for decentralized implementations because they carry less implementation and engagement challenges than centralized ones. Simultaneously, due to decentralized systems' interoperability issues, federated implementations (with a set of national standards) might be preferable. CONCLUSION This study identifies the primary socio-technical, legal, and ethical factors that challenge and contribute to the success of eHealth system implementations. This study also describes the complexities and characteristics of existing eHealth implementation programs, and suggests guidance for resolving the identified challenges.
Collapse
Affiliation(s)
- James Scheibner
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland.,College of Business, Government and Law, Flinders University, Adelaide, Australia
| | - Joanna Sleigh
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland
| | - Marcello Ienca
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland
| | - Effy Vayena
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland
| |
Collapse
|
9
|
Zuk P, Sanchez CE, Kostick K, Torgerson L, Muñoz KA, Hsu R, Kalwani L, Sierra-Mercado D, Robinson JO, Outram S, Koenig BA, Pereira S, McGuire AL, Lázaro-Muñoz G. Researcher Perspectives on Data Sharing in Deep Brain Stimulation. Front Hum Neurosci 2021; 14:578687. [PMID: 33424563 PMCID: PMC7793701 DOI: 10.3389/fnhum.2020.578687] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 11/16/2020] [Indexed: 01/21/2023] Open
Abstract
The expansion of research on deep brain stimulation (DBS) and adaptive DBS (aDBS) raises important neuroethics and policy questions related to data sharing. However, there has been little empirical research on the perspectives of experts developing these technologies. We conducted semi-structured, open-ended interviews with aDBS researchers regarding their data sharing practices and their perspectives on ethical and policy issues related to sharing. Researchers expressed support for and a commitment to sharing, with most saying that they were either sharing their data or would share in the future and that doing so was important for advancing the field. However, those who are sharing reported a variety of sharing partners, suggesting heterogeneity in sharing practices and lack of the broad sharing that would reflect principles of open science. Researchers described several concerns and barriers related to sharing, including privacy and confidentiality, the usability of shared data by others, ownership and control of data (including potential commercialization), and limited resources for sharing. They also suggested potential solutions to these challenges, including additional safeguards to address privacy issues, standardization and transparency in analysis to address issues of data usability, professional norms and heightened cooperation to address issues of ownership and control, and streamlining of data transmission to address resource limitations. Researchers also offered a range of views on the sensitivity of neural activity data (NAD) and data related to mental health in the context of sharing. These findings are an important input to deliberations by researchers, policymakers, neuroethicists, and other stakeholders as they navigate ethics and policy questions related to aDBS research.
Collapse
Affiliation(s)
- Peter Zuk
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Clarissa E Sanchez
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Kristin Kostick
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Laura Torgerson
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Katrina A Muñoz
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Rebecca Hsu
- Evans School of Public Policy and Governance, University of Washington, Seattle, WA, United States
| | - Lavina Kalwani
- Department of Biosciences, Rice University, Houston, TX, United States
| | - Demetrio Sierra-Mercado
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States.,Department of Anatomy and Neurobiology, School of Medicine, University of Puerto Rico, San Juan, Puerto Rico
| | - Jill O Robinson
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Simon Outram
- Program in Bioethics, University of California, San Francisco, San Francisco, CA, United States
| | - Barbara A Koenig
- Program in Bioethics, University of California, San Francisco, San Francisco, CA, United States
| | - Stacey Pereira
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Amy L McGuire
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Gabriel Lázaro-Muñoz
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| |
Collapse
|
10
|
Parker W, Jaremko JL, Cicero M, Azar M, El-Emam K, Gray BG, Hurrell C, Lavoie-Cardinal F, Desjardins B, Lum A, Sheremeta L, Lee E, Reinhold C, Tang A, Bromwich R. Canadian Association of Radiologists White Paper on De-Identification of Medical Imaging: Part 1, General Principles. Can Assoc Radiol J 2020; 72:13-24. [PMID: 33138621 DOI: 10.1177/0846537120967349] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 1 of this article will inform CAR members on principles of de-identification, pseudonymization, encryption, direct and indirect identifiers, k-anonymization, risks of reidentification, implementations, data set release models, and validation of AI algorithms, with a view to developing appropriate standards to safeguard patient information effectively.
Collapse
Affiliation(s)
- William Parker
- Department of Radiology, 8166University of British Columbia, Vancouver, British Columbia, Canada.,SapienML Corp, Vancouver, British Columbia, Canada
| | - Jacob L Jaremko
- Department of Radiology & Diagnostic Imaging, 12357University of Alberta, Edmonton, Canada
| | - Mark Cicero
- 16 Bit Inc, Toronto, Ontario, Canada.,True North Imaging, Thornhill, Ontario, Canada
| | - Marleine Azar
- Department of Medicine, 5622Université de Montréal, Montréal, Quebec, Canada
| | - Khaled El-Emam
- School of Epidemiology and Public Health, University of Ottawa, Ontario, Canada
| | - Bruce G Gray
- Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Casey Hurrell
- 525917Canadian Association of Radiologists, Ottawa, Canada
| | | | | | - Andrea Lum
- Department of Medical Imaging, 6221Western University, London, Ontario, Canada
| | - Lori Sheremeta
- 41464Northern Alberta Institute of Technology, Alberta, Canada
| | - Emil Lee
- 27355Fraser Health Authority, Vancouver, British Columbia, Canada
| | - Caroline Reinhold
- 54473McGill University Health Center, McGill University, Montreal, Canada.,Augmented Intelligence & Precision Health Laboratory of the Research Institute, McGill University Health Center, McGill University, Montreal, Canada
| | - An Tang
- Department of Radiology, Radio-oncology, and Nuclear Medicine, 5622Universite de Montreal, Montreal, Quebec, Canada
| | - Rebecca Bromwich
- Department of Law and Legal Studies, 6339Carleton University, Ottawa, Canada
| |
Collapse
|
11
|
Rahimzadeh V, Knoppers BM, Bartlett G. Ethical, Legal, and Social Issues (ELSI) of Responsible Data Sharing Involving Children in Genomics: A Systematic Literature Review of Reasons. AJOB Empir Bioeth 2020; 11:233-245. [PMID: 32975491 DOI: 10.1080/23294515.2020.1818875] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
BACKGROUND Progress in precision medicine relies on the access to, use of, and exchange of genomic and associated clinical data, including from children. The ethical, legal, and social issues (ELSI) of such data access, use, and exchange may be accentuated in the pediatric context due in part to the highly sensitive nature of genomic data, children's consent-related vulnerabilities, and uncertain risks of reidentification. Systematic analyses of the ELSI and scientific reasons for why and how genomic data may be shared responsibly are, however, limited. Methods: We conducted a modified systematic review of reasons according to Sofaer and Strech to examine the ELSI and scientific reasons for "responsible" sharing of children's genomic and associated clinical data. Empirical articles, commentaries, and data-sharing policies indexed in Medline, Scopus, Web of Science, and BIOSIS were included in the analysis if they discussed ELSI and were published between 2003 and 2017 in English. Results: One hundred and fifty-one records met our inclusion criteria. We identified 11 unique reasons and 8 subreasons for why children's genomic data should or should not be shared. Enhancing the prospect of direct and indirect benefits and maximizing the utility of children's data were top reasons why data should be shared. Inadequate data privacy protection was the leading reason why it should not. We furthermore identified 8 reasons and 30 subreasons that support conditional data sharing, in which recontact for the continued use of children's data once they reach the age of majority was the most frequently endorsed condition. Conclusions: The complete list of ELSI reasons and responsible conditions provides an evidentiary basis upon which institutions can develop data-sharing policies. Institutions should encourage the sharing of children's data to advance genomic research, while heeding special reconsent and data protection mechanisms that may help mitigate uncertain longitudinal risks for children and families.
Collapse
Affiliation(s)
- Vasiliki Rahimzadeh
- Center for Biomedical Ethics, Stanford University, Stanford, California, USA
| | | | | |
Collapse
|
12
|
Jacquemard T, Doherty CP, Fitzsimons MB. Examination and diagnosis of electronic patient records and their associated ethics: a scoping literature review. BMC Med Ethics 2020; 21:76. [PMID: 32831076 PMCID: PMC7446190 DOI: 10.1186/s12910-020-00514-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 08/03/2020] [Indexed: 02/22/2023] Open
Abstract
Background Electronic patient record (EPR) technology is a key enabler for improvements to healthcare service and management. To ensure these improvements and the means to achieve them are socially and ethically desirable, careful consideration of the ethical implications of EPRs is indicated. The purpose of this scoping review was to map the literature related to the ethics of EPR technology. The literature review was conducted to catalogue the prevalent ethical terms, to describe the associated ethical challenges and opportunities, and to identify the actors involved. By doing so, it aimed to support the future development of ethics guidance in the EPR domain. Methods To identify journal articles debating the ethics of EPRs, Scopus, Web of Science, and PubMed academic databases were queried and yielded 123 eligible articles. The following inclusion criteria were applied: articles need to be in the English language; present normative arguments and not solely empirical research; include an abstract for software analysis; and discuss EPR technology. Results The medical specialty, type of information captured and stored in EPRs, their use and functionality varied widely across the included articles. Ethical terms extracted were categorised into clusters ‘privacy’, ‘autonomy’, ‘risk/benefit’, ‘human relationships’, and ‘responsibility’. The literature shows that EPR-related ethical concerns can have both positive and negative implications, and that a wide variety of actors with rights and/or responsibilities regarding the safe and ethical adoption of the technology are involved. Conclusions While there is considerable consensus in the literature regarding EPR-related ethical principles, some of the associated challenges and opportunities remain underdiscussed. For example, much of the debate is presented in a manner more in keeping with a traditional model of healthcare and fails to take account of the multidimensional ensemble of factors at play in the EPR era and the consequent need to redefine/modify ethical norms to align with a digitally-enabled health service. Similarly, the academic discussion focuses predominantly on bioethical values. However, approaches from digital ethics may also be helpful to identify and deliberate about current and emerging EPR-related ethical concerns.
Collapse
Affiliation(s)
- Tim Jacquemard
- FutureNeuro, the SFI Research Centre for Chronic and Rare Neurological Diseases, 123 Stephen's Green, Dublin 2, Ireland.
| | - Colin P Doherty
- FutureNeuro, the SFI Research Centre for Chronic and Rare Neurological Diseases, 123 Stephen's Green, Dublin 2, Ireland.,Department of Neurology, St. James's Hospital, James's Street, Dublin 8, Ireland.,Trinity College Dublin, College Green, Dublin 2, Ireland
| | - Mary B Fitzsimons
- FutureNeuro, the SFI Research Centre for Chronic and Rare Neurological Diseases, 123 Stephen's Green, Dublin 2, Ireland
| |
Collapse
|
13
|
Sirdah MM, Reading NS. Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes. Clin Genet 2020; 98:525-547. [PMID: 32385895 DOI: 10.1111/cge.13772] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 05/04/2020] [Accepted: 05/04/2020] [Indexed: 02/06/2023]
Abstract
Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.
Collapse
Affiliation(s)
- Mahmoud M Sirdah
- Division of Hematology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA.,Biology Department, Al Azhar University-Gaza, Gaza, Palestine
| | - N Scott Reading
- Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA.,Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA
| |
Collapse
|
14
|
Abstract
This work provides an overview of a Spanish survey on research data, which was carried out within the framework of the project Datasea at the beginning of 2015. It is covered by the objectives of sustainable development (goal 9) to support the research. The purpose of the study was to identify the habits and current experiences of Spanish researchers in the health sciences in relation to the management and sharing of raw research data. Method: An electronic questionnaire composed of 40 questions divided into three blocks was designed. The three Section s contained questions on the following aspects: (A) personal information; (B) creation and reuse of data; and (C) preservation of data. The questionnaire was sent by email to a list of universities in Spain to be distributed among their researchers and professors. A total of 1063 researchers completed the questionnaire. More than half of the respondents (54.9%) lacked a data management plan; nearly a quarter had storage systems for the research group; 81.5% used personal computers to store data; “Contact with colleagues” was the most frequent means used to locate and access other researchers’ data; and nearly 60% of researchers stated their data were available to the research group and collaborating colleagues. The main fears about sharing were legal questions (47.9%), misuse or interpretation of data (42.7%), and loss of authorship (28.7%). The results allow us to understand the state of data sharing among Spanish researchers and can serve as a basis to identify the needs of researchers to share data, optimize existing infrastructure, and promote data sharing among those who do not practice it yet.
Collapse
|
15
|
Long NP, Nghi TD, Kang YP, Anh NH, Kim HM, Park SK, Kwon SW. Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine. Metabolites 2020; 10:E51. [PMID: 32013105 PMCID: PMC7074059 DOI: 10.3390/metabo10020051] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/17/2020] [Accepted: 01/21/2020] [Indexed: 12/18/2022] Open
Abstract
Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.
Collapse
Affiliation(s)
- Nguyen Phuoc Long
- College of Pharmacy, Seoul National University, Seoul 08826, Korea; (N.P.L.); (N.H.A.); (H.M.K.)
| | - Tran Diem Nghi
- Department of Life Sciences, Pohang University of Science and Technology, Pohang 790-784, Korea; (T.D.N.); (S.K.P.)
| | - Yun Pyo Kang
- Department of Cancer Physiology, Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA;
| | - Nguyen Hoang Anh
- College of Pharmacy, Seoul National University, Seoul 08826, Korea; (N.P.L.); (N.H.A.); (H.M.K.)
| | - Hyung Min Kim
- College of Pharmacy, Seoul National University, Seoul 08826, Korea; (N.P.L.); (N.H.A.); (H.M.K.)
| | - Sang Ki Park
- Department of Life Sciences, Pohang University of Science and Technology, Pohang 790-784, Korea; (T.D.N.); (S.K.P.)
| | - Sung Won Kwon
- College of Pharmacy, Seoul National University, Seoul 08826, Korea; (N.P.L.); (N.H.A.); (H.M.K.)
| |
Collapse
|
16
|
Lightbody G, Haberland V, Browne F, Taggart L, Zheng H, Parkes E, Blayney JK. Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application. Brief Bioinform 2019; 20:1795-1811. [PMID: 30084865 PMCID: PMC6917217 DOI: 10.1093/bib/bby051] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 05/01/2018] [Indexed: 12/28/2022] Open
Abstract
There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.
Collapse
Affiliation(s)
- Gaye Lightbody
- School of Computing, Ulster University, Newtownabbey, UK
| | - Valeriia Haberland
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Fiona Browne
- School of Computing, Ulster University, Newtownabbey, UK
| | | | - Huiru Zheng
- School of Computing, Ulster University, Newtownabbey, UK
| | - Eileen Parkes
- Centre for Cancer Research & Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
| | - Jaine K Blayney
- Centre for Cancer Research & Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
| |
Collapse
|
17
|
Manhas KP, Dodd SX, Page S, Letourneau N, Adair CE, Cui X, Tough SC. Sharing longitudinal, non-biological birth cohort data: a cross-sectional analysis of parent consent preferences. BMC Med Inform Decis Mak 2018; 18:97. [PMID: 30419910 PMCID: PMC6233367 DOI: 10.1186/s12911-018-0683-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 10/19/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mandates abound to share publicly-funded research data for reuse, while data platforms continue to emerge to facilitate such reuse. Birth cohorts (BC) involve longitudinal designs, significant sample sizes and rich and deep datasets. Data sharing benefits include more analyses, greater research complexity, increased opportunities for collaboration, amplification of public contributions, and reduced respondent burdens. Sharing BC data involves significant challenges including consent, privacy, access policies, communication, and vulnerability of the child. Research on these issues is available for biological data, but these findings may not extend to BC data. We lack consensus on how best to approach these challenges in consent, privacy, communication and autonomy when sharing BC data. We require more stakeholder engagement to understand perspectives and generate consensus. METHODS Parents participating in longitudinal birth cohorts completed a web-based survey investigating consent preferences for sharing their, and their child's, non-biological research data. Results from a previous qualitative inquiry informed survey development, and cognitive interviewing methods (n = 9) were used to improve the question quality and comprehension. Recruitment was via personalized email, with email and phone reminders during the 14-day window for survey completion. RESULTS Three hundred and forty-six of 569 parents completed the survey in September 2014 (60.8%). Participants preferred consent processes for data sharing in future independent research that were less-active (i.e. no consent or opt-out). Parents' consent preferences are associated with their communication preferences. Twenty percent (20.2%) of parents generally agreed that their child should provide consent to continue participating in research at age 12, while 25.6% felt decision-making on sharing non-biological research data should begin at age 18. CONCLUSIONS These finding reflect the parenting population's preference for less project-specific permission when research data is non-biological and de-identified and when governance practices are highly detailed and rigourous. Parents recognize that children should become involved in consent for secondary data use, but there is variability regarding when and how involvement occurs. These findings emphasize governance processes and participant notification rather than project-specific consent for secondary use of de-identified, non-biological data. Ultimately, parents prefer general consent processes for sharing de-identified, non-biological research data with ultimate involvement of the child.
Collapse
Affiliation(s)
- Kiran Pohar Manhas
- Community Health Sciences, University of Calgary, Calgary, Canada
- University of Alberta, Edmonton, Canada
- Alberta Health Services, Calgary, Canada
| | | | - Stacey Page
- Community Health Sciences, University of Calgary, Calgary, Canada
- Conjoint Health Research Ethics Board, University of Calgary, Calgary, Canada
| | | | - Carol E. Adair
- Community Health Sciences, University of Calgary, Calgary, Canada
| | - Xinjie Cui
- PolicyWise for Children & Families, Edmonton, AB Canada
| | - Suzanne C. Tough
- PolicyWise for Children & Families, Calgary, Canada
- Pediatrics & Community Health Sciences, University of Calgary, Calgary, Canada
| |
Collapse
|
18
|
Abstract
Pharmacogenomics is a tool for practitioners to provide precision pharmacotherapy using genomics. All providers are likely to encounter genomic data in practice with the expectation that they are able to successfully apply it to patient care. Pharmacogenomics tests for genetic variations in genes that are responsible for drug metabolism, transport, and targets of drug action. Variations can increase the risk for drug toxicity or poor efficacy. Pharmacogenomics can, therefore, be used to help select the best medication or aid in dosing. Nephrologists routinely treat cardiovascular disease and manage patients after kidney transplantation, two situations for which there are several high-evidence clinical recommendations for commonly used anticoagulants, antiplatelets, statins, and transplant medications. Successful use of pharmacogenomics in practice requires that providers are familiar with how to access and use pharmacogenomics resources. Similarly, clinical decision making related to whether to use existing data, whether to order testing, and if data should be used in practice is needed to deliver precision medicine. Pharmacogenomics is applicable to virtually every medical specialty, and nephrologists are well positioned to be implementation leaders.
Collapse
Affiliation(s)
| | | | - Philip E. Empey
- Department of Pharmacy and Therapeutics, School of Pharmacy, and
- Institute and of Precision Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| |
Collapse
|
19
|
Sharing data for future research-engaging participants' views about data governance beyond the original project: a DIRECT Study. Genet Med 2018; 21:1131-1138. [PMID: 30262927 DOI: 10.1038/s41436-018-0299-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 08/30/2018] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Biomedical data governance strategies should ensure that data are collected, stored, and used ethically and lawfully. However, research participants' preferences for how data should be governed is least studied. The Diabetes Research on Patient Stratification (DIRECT) project collected substantial amounts of health and genetic information from patients at risk of, and with type II diabetes. We conducted a survey to understand participants' future data governance preferences. Results will inform the postproject data governance strategy. METHODS A survey was distributed in Denmark, Sweden, The Netherlands, and the United Kingdom. RESULTS In total 855 surveys were returned. Ninety-seven percent were supportive of sharing data postproject, and 90% were happy to share data with universities, and 56% with commercial companies. The top three priorities for data sharing were highly secure database, DIRECT researchers to monitor data used by other researchers, and researchers cannot identify participants. Respondents frequently suggested that a postproject Data Access Committee should involve a DIRECT researcher, diabetes clinician, patient representative, and a DIRECT participant. CONCLUSION Preferences of how data should be governed, and what data could be shared and with whom varied between countries. Researchers are considered as key custodians of participant data. Engaging participants aids in designing governance to support their choices.
Collapse
|
20
|
Goldenberg A, Brothers K. Misplaced Trust: Building Research Relationships in the Age of Biorepository Networks. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2018; 18:21-23. [PMID: 29621469 DOI: 10.1080/15265161.2018.1431330] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
|
21
|
Klein ME, Parvez MM, Shin JG. Clinical Implementation of Pharmacogenomics for Personalized Precision Medicine: Barriers and Solutions. J Pharm Sci 2017; 106:2368-2379. [DOI: 10.1016/j.xphs.2017.04.051] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 04/14/2017] [Accepted: 04/24/2017] [Indexed: 12/11/2022]
|
22
|
Takai-Igarashi T, Kinoshita K, Nagasaki M, Ogishima S, Nakamura N, Nagase S, Nagaie S, Saito T, Nagami F, Minegishi N, Suzuki Y, Suzuki K, Hashizume H, Kuriyama S, Hozawa A, Yaegashi N, Kure S, Tamiya G, Kawaguchi Y, Tanaka H, Yamamoto M. Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design. BMC Med Inform Decis Mak 2017; 17:100. [PMID: 28683736 PMCID: PMC5501115 DOI: 10.1186/s12911-017-0494-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 06/27/2017] [Indexed: 01/08/2023] Open
Abstract
Background With the goal of realizing genome-based personalized healthcare, we have developed a biobank that integrates personal health, genome, and omics data along with biospecimens donated by volunteers of 150,000. Such a large-scale of data integration involves obvious risks of privacy violation. The research use of personal genome and health information is a topic of global discussion with regard to the protection of privacy while promoting scientific advancement. The present paper reports on our plans, current attempts, and accomplishments in addressing security problems involved in data sharing to ensure donor privacy while promoting scientific advancement. Methods Biospecimens and data have been collected in prospective cohort studies with the comprehensive agreement. The sample size of 150,000 participants was required for multiple researches including genome-wide screening of gene by environment interactions, haplotype phasing, and parametric linkage analysis. Results We established the TohokuMedicalMegabank (TMM) data sharing policy: a privacy protection rule that requires physical, personnel, and technological safeguards against privacy violation regarding the use and sharing of data. The proposed policy refers to that of NCBI and that of the Sanger Institute. The proposed policy classifies shared data according to the strength of re-identification risks. Local committees organized by TMM evaluate re-identification risk and assign a security category to a dataset. Every dataset is stored in an assigned segment of a supercomputer in accordance with its security category. A security manager should be designated to handle all security problems at individual data use locations. The proposed policy requires closed networks and IP-VPN remote connections. Conclusion The mission of the biobank is to distribute biological resources most productively. This mission motivated us to collect biospecimens and health data and simultaneously analyze genome/omics data in-house. The biobank also has the mission of improving the quality and quantity of the contents of the biobank. This motivated us to request users to share the results of their research as feedback to the biobank. The TMM data sharing policy has tackled every security problem originating with the missions. We believe our current implementation to be the best way to protect privacy in data sharing. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0494-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Takako Takai-Igarashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Naoki Nakamura
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Sachiko Nagase
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Satoshi Nagaie
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Tomo Saito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Fuji Nagami
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yoichi Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Kichiya Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Hiroaki Hashizume
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Yoshio Kawaguchi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Hiroshi Tanaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan. .,Graduate School of Medicine, Tohoku University, Sendai, Japan.
| |
Collapse
|
23
|
Brandizi M, Melnichuk O, Bild R, Kohlmayer F, Rodriguez-Castro B, Spengler H, Kuhn KA, Kuchinke W, Ohmann C, Mustonen T, Linden M, Nyrönen T, Lappalainen I, Brazma A, Sarkans U. Orchestrating differential data access for translational research: a pilot implementation. BMC Med Inform Decis Mak 2017; 17:30. [PMID: 28330491 PMCID: PMC5363029 DOI: 10.1186/s12911-017-0424-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 03/03/2017] [Indexed: 01/30/2023] Open
Abstract
Background Translational researchers need robust IT solutions to access a range of data types, varying from public data sets to pseudonymised patient information with restricted access, provided on a case by case basis. The reason for this complication is that managing access policies to sensitive human data must consider issues of data confidentiality, identifiability, extent of consent, and data usage agreements. All these ethical, social and legal aspects must be incorporated into a differential management of restricted access to sensitive data. Methods In this paper we present a pilot system that uses several common open source software components in a novel combination to coordinate access to heterogeneous biomedical data repositories containing open data (open access) as well as sensitive data (restricted access) in the domain of biobanking and biosample research. Our approach is based on a digital identity federation and software to manage resource access entitlements. Results Open source software components were assembled and configured in such a way that they allow for different ways of restricted access according to the protection needs of the data. We have tested the resulting pilot infrastructure and assessed its performance, feasibility and reproducibility. Conclusions Common open source software components are sufficient to allow for the creation of a secure system for differential access to sensitive data. The implementation of this system is exemplary for researchers facing similar requirements for restricted access data. Here we report experience and lessons learnt of our pilot implementation, which may be useful for similar use cases. Furthermore, we discuss possible extensions for more complex scenarios.
Collapse
Affiliation(s)
- Marco Brandizi
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.
| | - Olga Melnichuk
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Raffael Bild
- Chair of Medical Informatics, Institute of Medical Statistics and Epidemiology, University Medical Center rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Kohlmayer
- Chair of Medical Informatics, Institute of Medical Statistics and Epidemiology, University Medical Center rechts der Isar, Technical University of Munich, Munich, Germany
| | - Benedicto Rodriguez-Castro
- Chair of Medical Informatics, Institute of Medical Statistics and Epidemiology, University Medical Center rechts der Isar, Technical University of Munich, Munich, Germany
| | - Helmut Spengler
- Chair of Medical Informatics, Institute of Medical Statistics and Epidemiology, University Medical Center rechts der Isar, Technical University of Munich, Munich, Germany
| | - Klaus A Kuhn
- Chair of Medical Informatics, Institute of Medical Statistics and Epidemiology, University Medical Center rechts der Isar, Technical University of Munich, Munich, Germany
| | - Wolfgang Kuchinke
- Heinrich-Heine Universität Düsseldorf, Coordination Centre for Clinical Trials, Düsseldorf, Germany
| | - Christian Ohmann
- European Clinical Research Infrastructure Network (ECRIN), Düsseldorf, Germany
| | | | | | | | | | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Ugis Sarkans
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.
| |
Collapse
|
24
|
Smith ME, Sanderson SC, Brothers KB, Myers MF, McCormick J, Aufox S, Shrubsole MJ, Garrison NA, Mercaldo ND, Schildcrout JS, Clayton EW, Antommaria AHM, Basford M, Brilliant M, Connolly JJ, Fullerton SM, Horowitz CR, Jarvik GP, Kaufman D, Kitchner T, Li R, Ludman EJ, McCarty C, McManus V, Stallings S, Williams JL, Holm IA. Conducting a large, multi-site survey about patients' views on broad consent: challenges and solutions. BMC Med Res Methodol 2016; 16:162. [PMID: 27881091 PMCID: PMC5122167 DOI: 10.1186/s12874-016-0263-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 11/11/2016] [Indexed: 11/28/2022] Open
Abstract
Background As biobanks play an increasing role in the genomic research that will lead to precision medicine, input from diverse and large populations of patients in a variety of health care settings will be important in order to successfully carry out such studies. One important topic is participants’ views towards consent and data sharing, especially since the 2011 Advanced Notice of Proposed Rulemaking (ANPRM), and subsequently the 2015 Notice of Proposed Rulemaking (NPRM) were issued by the Department of Health and Human Services (HHS) and Office of Science and Technology Policy (OSTP). These notices required that participants consent to research uses of their de-identified tissue samples and most clinical data, and allowing such consent be obtained in a one-time, open-ended or “broad” fashion. Conducting a survey across multiple sites provides clear advantages to either a single site survey or using a large online database, and is a potentially powerful way of understanding the views of diverse populations on this topic. Methods A workgroup of the Electronic Medical Records and Genomics (eMERGE) Network, a national consortium of 9 sites (13 separate institutions, 11 clinical centers) supported by the National Human Genome Research Institute (NHGRI) that combines DNA biorepositories with electronic medical record (EMR) systems for large-scale genetic research, conducted a survey to understand patients’ views on consent, sample and data sharing for future research, biobank governance, data protection, and return of research results. Results Working across 9 sites to design and conduct a national survey presented challenges in organization, meeting human subjects guidelines at each institution, and survey development and implementation. The challenges were met through a committee structure to address each aspect of the project with representatives from all sites. Each committee’s output was integrated into the overall survey plan. A number of site-specific issues were successfully managed allowing the survey to be developed and implemented uniformly across 11 clinical centers. Conclusions Conducting a survey across a number of institutions with different cultures and practices is a methodological and logistical challenge. With a clear infrastructure, collaborative attitudes, excellent lines of communication, and the right expertise, this can be accomplished successfully.
Collapse
Affiliation(s)
- Maureen E Smith
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Avenue, Chicago, IL, 60611, USA.
| | - Saskia C Sanderson
- Icahn School of Medicine at Mount Sinai, New York, NY, USA.,University College London, London, UK
| | - Kyle B Brothers
- University of Louisville School of Medicine, Louisville, KY, USA
| | - Melanie F Myers
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Sharon Aufox
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Avenue, Chicago, IL, 60611, USA
| | - Martha J Shrubsole
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Nathaniel D Mercaldo
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Ellen Wright Clayton
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Melissa Basford
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - John J Connolly
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | | | | | - Dave Kaufman
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Terri Kitchner
- Marshfield Clinic Research Foundation, Marshfield, WI, USA
| | - Rongling Li
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | | | | | - Sarah Stallings
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Ingrid A Holm
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
25
|
Kraft SA, Cho MK, Constantine M, Lee SSJ, Kelley M, Korngiebel D, James C, Kuwana E, Meyer A, Porter K, Diekema D, Capron AM, Alicic R, Wilfond BS, Magnus D. A comparison of institutional review board professionals' and patients' views on consent for research on medical practices. Clin Trials 2016; 13:555-65. [PMID: 27257125 PMCID: PMC5025342 DOI: 10.1177/1740774516648907] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND/AIMS In the context of research on medical practices, which includes comparative effectiveness research and pragmatic clinical trials, empirical studies have begun to raise questions about the extent to which institutional review boards' interpretations and applications of research regulations align with patients' values. To better understand the similarities and differences between these stakeholder groups, we compare and contrast two surveys: one of institutional review board professionals and one of patients, which examine views on consent for research on medical practices. METHODS We conducted online surveys of two target populations between July 2014 and March 2015. We surveyed 601 human subjects research professionals out of 1500 randomly selected from the Public Responsibility in Medicine and Research membership list (40.1% response rate), limiting analysis to 537 respondents who reported having had institutional review board experience. We also surveyed 120 adult patients out of 225 approached at subspecialty clinics in Spokane, Washington (53.3% response rate). Our survey questions probed attitudes about consent in the context of research on medical practices using medical record review and randomization. The patient survey included three embedded animated videos to explain these concepts. RESULTS A majority of institutional review board professionals distinguished between consent preferences for medical record review and randomization, ranked clinicians as the least preferred person to obtain participant consent (54.6%), and viewed written or verbal permission as the minimum acceptable consent approach for research on medical practices using randomization (87.3%). In contrast, most patients had similar consent preferences for research on medical practices using randomization and medical record review, most preferred to have consent conversations with their doctors rather than with researchers for studies using randomization (72.6%) and medical record review (67.0%), and only a few preferred to see research involving randomization (16.8%) or medical record review (13.8%) not take place if obtaining written or verbal permission would make the research too difficult to conduct. Limitations of our post hoc analysis include differences in framing, structure, and language between the two surveys and possible response bias. CONCLUSION Our findings highlight a need to identify appropriate ways to integrate patient preferences into prevailing regulatory interpretations as institutional review boards increasingly apply research regulations in the context of research on medical practices. Dialogue between institutional review boards and research participants will be an important part of this process and should inform future regulatory guidance.
Collapse
Affiliation(s)
| | - Mildred K Cho
- Stanford Center for Biomedical Ethics, Stanford, CA, USA
| | - Melissa Constantine
- Division of Health Policy and Management, University of Minnesota, Minneapolis, MN, USA
| | | | - Maureen Kelley
- Ethox Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Diane Korngiebel
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Cyan James
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Ellen Kuwana
- Treuman Katz Center for Pediatric Bioethics, Seattle Children's Research Institute, Seattle, WA, USA
| | - Adrienne Meyer
- Human Subjects Division, University of Washington, Seattle, WA, USA
| | - Kathryn Porter
- Treuman Katz Center for Pediatric Bioethics, Seattle Children's Research Institute, Seattle, WA, USA
| | - Douglas Diekema
- Treuman Katz Center for Pediatric Bioethics, Seattle Children's Research Institute, Seattle, WA, USA
| | - Alexander M Capron
- USC Gould School of Law, University of Southern California, Los Angeles, CA, USA
| | - Radica Alicic
- Providence Medical Research Center, Spokane, WA, USA
| | - Benjamin S Wilfond
- Treuman Katz Center for Pediatric Bioethics, Seattle Children's Research Institute, Seattle, WA, USA
| | - David Magnus
- Stanford Center for Biomedical Ethics, Stanford, CA, USA
| |
Collapse
|
26
|
Condit CM, Shen L, Edwards KL, Bowen DJ, Korngiebel DM, Johnson CO. Participants' Role Expectations in Genetics Research and Re-consent: Revising the Theory and Methods of Mental Models Research Relating to Roles. JOURNAL OF HEALTH COMMUNICATION 2016; 21:16-24. [PMID: 27653592 PMCID: PMC7868084 DOI: 10.1080/10810730.2016.1193914] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The rise of large cohort-based health research that includes genetic components has increased the communication challenges for researchers. Controversies have been amplified over requirements for re-consent, return of results, and privacy protections, among other issues. This study extended research on the impact that the perceived role of "research participant" might have on communication expectations to illuminate research participants' preferences for re-consent. The study employed an online survey of participants in a long-standing cancer genetics registry. Results confirmed previous exploratory findings that research participants endorse multiple mental models of participant roles in research (doctor-patient, collaborator, donor, legal contract, etc.). Regression analyses indicated that high and low salience of different models of the role of research participant are related to different communication expectations. However, the pattern of relationships among roles is relevant. The results of the regression analysis also indicated that preference for mandatory re-consent and its relationship to mental models of roles are related to attitudes of trust, benefits, and informational risks. The discussion identifies implications as including the use of explicit approaches to address role relationships in communication with research participants. It also points to implications for methodological approaches in mental model research.
Collapse
Affiliation(s)
- Celeste M Condit
- a Department of Communication Studies , University of Georgia , Athens , Georgia , USA
| | - Lijiang Shen
- b Department of Communication Arts and Sciences , Pennsylvania State University , University Park , Pennsylvania , USA
| | - Karen L Edwards
- c Department of Epidemiology, School of Medicine , University of California, Irvine , Irvine , California , USA
| | - Deborah J Bowen
- d Department of Bioethics and Humanities , University of Washington , Seattle , Washington , USA
| | - Diane M Korngiebel
- e Biomedical Informatics and Medical Education , University of Washington , Seattle , Washington , USA
| | - Catherine O Johnson
- c Department of Epidemiology, School of Medicine , University of California, Irvine , Irvine , California , USA
| |
Collapse
|
27
|
O'Doherty KC, Christofides E, Yen J, Bentzen HB, Burke W, Hallowell N, Koenig BA, Willison DJ. If you build it, they will come: unintended future uses of organised health data collections. BMC Med Ethics 2016; 17:54. [PMID: 27600117 PMCID: PMC5011895 DOI: 10.1186/s12910-016-0137-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Accepted: 08/25/2016] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Health research increasingly relies on organized collections of health data and biological samples. There are many types of sample and data collections that are used for health research, though these are collected for many purposes, not all of which are health-related. These collections exist under different jurisdictional and regulatory arrangements and include: 1) Population biobanks, cohort studies, and genome databases 2) Clinical and public health data 3) Direct-to-consumer genetic testing 4) Social media 5) Fitness trackers, health apps, and biometric data sensors Ethical, legal, and social challenges of such collections are well recognized, but there has been limited attention to the broader societal implications of the existence of these collections. DISCUSSION Although health research conducted using these collections is broadly recognized as beneficent, secondary uses of these data and samples may be controversial. We examine both documented and hypothetical scenarios of secondary uses of health data and samples. In particular, we focus on the use of health data for purposes of: Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes CONCLUSIONS Current safeguards relating to the use of health data and samples include research ethics oversight and privacy laws. These safeguards have a strong focus on informed consent and anonymization, which are aimed at the protection of the individual research subject. They are not intended to address broader societal implications of health data and sample collections. As such, existing arrangements are insufficient to protect against subversion of health databases for non-sanctioned secondary uses, or to provide guidance for reasonable but controversial secondary uses. We are concerned that existing debate in the scholarly literature and beyond has not sufficiently recognized the secondary data uses we outline in this paper. Our main purpose, therefore, is to raise awareness of the potential for unforeseen and unintended consequences, in particular negative consequences, of the increased availability and development of health data collections for research, by providing a comprehensive review of documented and hypothetical non-health research uses of such data.
Collapse
Affiliation(s)
- Kieran C O'Doherty
- Department of Psychology, University of Guelph, Guelph, ON, N1G 2W1, Canada.
| | - Emily Christofides
- Department of Psychology, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Jeffery Yen
- Department of Psychology, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Heidi Beate Bentzen
- Centre for Medical Ethics, Faculty of Medicine, University of Oslo, Oslo, Norway
- Norwegian Research Center for Computers and Law, Faculty of Law, University of Oslo, Oslo, Norway
- Norwegian Cancer Genomics Consortium, Oslo, Norway
| | - Wylie Burke
- Department of Bioethics & Humanities, University of Washington, Seattle, USA
| | - Nina Hallowell
- Ethox Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Barbara A Koenig
- UCSF Bioethics, Institute for Health & Aging, University of California, San Francisco, USA
| | - Donald J Willison
- Institute of Health Policy Management and Evaluation | Joint Centre for Bioethics, University of Toronto, Toronto, Canada
- Department of Clinical Epidemiology and Biostatistics, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| |
Collapse
|
28
|
Plis SM, Sarwate AD, Wood D, Dieringer C, Landis D, Reed C, Panta SR, Turner JA, Shoemaker JM, Carter KW, Thompson P, Hutchison K, Calhoun VD. COINSTAC: A Privacy Enabled Model and Prototype for Leveraging and Processing Decentralized Brain Imaging Data. Front Neurosci 2016; 10:365. [PMID: 27594820 PMCID: PMC4990563 DOI: 10.3389/fnins.2016.00365] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 07/22/2016] [Indexed: 01/17/2023] Open
Abstract
The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements). There are also significant data transfer, organization and computational challenges. Centralized repositories only partially address the issues. We propose a dynamic, decentralized platform for large scale analyses called the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). The COINSTAC solution can include data missing from central repositories, allows pooling of both open and "closed" repositories by developing privacy-preserving versions of widely-used algorithms, and incorporates the tools within an easy-to-use platform enabling distributed computation. We present an initial prototype system which we demonstrate on two multi-site data sets, without aggregating the data. In addition, by iterating across sites, the COINSTAC model enables meta-analytic solutions to converge to "pooled-data" solutions (i.e., as if the entire data were in hand). More advanced approaches such as feature generation, matrix factorization models, and preprocessing can be incorporated into such a model. In sum, COINSTAC enables access to the many currently unavailable data sets, a user friendly privacy enabled interface for decentralized analysis, and a powerful solution that complements existing data sharing solutions.
Collapse
Affiliation(s)
- Sergey M. Plis
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Anand D. Sarwate
- Department of Electrical and Computer Engineering, Rutgers, The State University of New JerseyPiscataway, NJ, USA
| | - Dylan Wood
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Christopher Dieringer
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Drew Landis
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Cory Reed
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Sandeep R. Panta
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Jessica A. Turner
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
- Department of Psychology and Neuroscience Institute, Georgia State UniversityAtlanta, GA, USA
| | - Jody M. Shoemaker
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
| | - Kim W. Carter
- Telethon Kids Institute, The University of Western AustraliaSubiaco, WA, Australia
| | - Paul Thompson
- Departments of Neurology, Psychiatry, Engineering, Radiology, and Pediatrics, Imaging Genetics Center, Enhancing Neuroimaging and Genetics through Meta-Analysis Center for Worldwide Medicine, Imaging, and Genomics, University of Southern CaliforniaMarina del Rey, CA, USA
| | - Kent Hutchison
- Department of Psychology and Neuroscience, University of Colorado BoulderBoulder, CO, USA
| | - Vince D. Calhoun
- The Mind Research Network, Lovelace Biomedical and Environmental Research InstituteAlbuquerque, NM, USA
- Department of Electrical and Computer Engineering, University of New MexicoAlbuquerque, NM, USA
| |
Collapse
|
29
|
Gupta J, Kanetsky PA, Wuttke M, Köttgen A, Schaefer F, Wong CS. Genome-wide association studies in pediatric chronic kidney disease. Pediatr Nephrol 2016; 31:1241-52. [PMID: 26490952 PMCID: PMC5287054 DOI: 10.1007/s00467-015-3235-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Revised: 09/20/2015] [Accepted: 09/22/2015] [Indexed: 01/13/2023]
Abstract
The genome-wide association study (GWAS) has become an established scientific method that provides an unbiased screen for genetic loci potentially associated with phenotypes of clinical interest, such as chronic kidney disease (CKD). Thus, GWAS provides opportunities to gain new perspectives regarding the genetic architecture of CKD progression by identifying new candidate genes and targets for intervention. As such, it has become an important arm of translational science providing a complementary line of investigation to identify novel therapeutics to treat CKD. In this review, we describe the method and the challenges of performing GWAS in the pediatric CKD population. We also provide an overview of successful GWAS for kidney disease, and we discuss the established pediatric CKD cohorts in North America and Europe that are poised to identify genetic risk variants associated with CKD progression.
Collapse
Affiliation(s)
- Jayanta Gupta
- Department of Biomedical Sciences, Texas Tech University Health Sciences Center, El Paso, TX, USA
| | - Peter A Kanetsky
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Matthias Wuttke
- Renal Division, Medical Center - University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Renal Division, Medical Center - University of Freiburg, Freiburg, Germany
| | - Franz Schaefer
- Pediatric Nephrology Division, University of Heidelberg, Heidelberg, Germany
| | - Craig S Wong
- Department of Pediatrics, Division of Nephrology, University of New Mexico Children's Hospital, MSC10-5590 1 University of New Mexico, Albuquerque, 87131-0001, NM, USA.
| |
Collapse
|
30
|
Roy S, LaFramboise WA, Nikiforov YE, Nikiforova MN, Routbort MJ, Pfeifer J, Nagarajan R, Carter AB, Pantanowitz L. Next-Generation Sequencing Informatics: Challenges and Strategies for Implementation in a Clinical Environment. Arch Pathol Lab Med 2016; 140:958-75. [PMID: 26901284 DOI: 10.5858/arpa.2015-0507-ra] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
CONTEXT -Next-generation sequencing (NGS) is revolutionizing the discipline of laboratory medicine, with a deep and direct impact on patient care. Although it empowers clinical laboratories with unprecedented genomic sequencing capability, NGS has brought along obvious and obtrusive informatics challenges. Bioinformatics and clinical informatics are separate disciplines with typically a small degree of overlap, but they have been brought together by the enthusiastic adoption of NGS in clinical laboratories. The result has been a collaborative environment for the development of novel informatics solutions. Sustaining NGS-based testing in a regulated clinical environment requires institutional support to build and maintain a practical, robust, scalable, secure, and cost-effective informatics infrastructure. OBJECTIVE -To discuss the novel NGS informatics challenges facing pathology laboratories today and offer solutions and future developments to address these obstacles. DATA SOURCES -The published literature pertaining to NGS informatics was reviewed. The coauthors, experts in the fields of molecular pathology, precision medicine, and pathology informatics, also contributed their experiences. CONCLUSIONS -The boundary between bioinformatics and clinical informatics has significantly blurred with the introduction of NGS into clinical molecular laboratories. Next-generation sequencing technology and the data derived from these tests, if managed well in the clinical laboratory, will redefine the practice of medicine. In order to sustain this progress, adoption of smart computing technology will be essential. Computational pathologists will be expected to play a major role in rendering diagnostic and theranostic services by leveraging "Big Data" and modern computing tools.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | - Liron Pantanowitz
- From the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Drs Roy, LaFramboise, Nikiforov, Nikiforova, and Pantanowitz); the Department of Pathology, MD Anderson Cancer Center, Houston, Texas (Dr Routbort); the Department of Pathology and Immunology, Washington University School of Medicine, St Louis, Missouri (Drs Pfeifer and Nagarajan); PierianDx, St Louis, Missouri (Dr Nagarajan); and the Department of Pathology and Laboratory Medicine, Children's Healthcare of Atlanta, Atlanta, Georgia (Dr Carter)
| |
Collapse
|
31
|
Shabani M, Knoppers BM, Borry P. From the principles of genomic data sharing to the practices of data access committees. EMBO Mol Med 2016; 7:507-9. [PMID: 25759363 PMCID: PMC4492813 DOI: 10.15252/emmm.201405002] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Sharing genomic research data through controlled-access databases has increased in recent years. Policymakers and funding organizations endorse genomic data sharing in order to optimize the use of public funds and to increase the statistical power of databases. Well-established data access arrangements and data access committees (DACs)-responsible for reviewing and managing requests for access to genomic databases-are therefore central for implementing the policies and principles of data sharing. This article aims to investigate the functionality of DACs through the perspective of existing practices.
Collapse
Affiliation(s)
- Mahsa Shabani
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
| | | | - Pascal Borry
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
| |
Collapse
|
32
|
Herr TM, Bielinski SJ, Bottinger E, Brautbar A, Brilliant M, Chute CG, Cobb BL, Denny JC, Hakonarson H, Hartzler AL, Hripcsak G, Kannry J, Kohane IS, Kullo IJ, Lin S, Manzi S, Marsolo K, Overby CL, Pathak J, Peissig P, Pulley J, Ralston J, Rasmussen L, Roden DM, Tromp G, Uphoff T, Weng C, Wolf W, Williams MS, Starren J. Practical considerations in genomic decision support: The eMERGE experience. J Pathol Inform 2015; 6:50. [PMID: 26605115 PMCID: PMC4629307 DOI: 10.4103/2153-3539.165999] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 07/23/2015] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presence of well-characterized drug-gene interactions. Clinical Decision Support (CDS) is an ideal avenue by which to implement PGx at the bedside. Previous literature has established theoretical models for PGx CDS implementation and discussed a number of anticipated real-world challenges. However, work detailing actual PGx CDS implementation experiences has been limited. Anticipated challenges include data storage and management, system integration, physician acceptance, and more. METHODS In this study, we analyzed the experiences of ten members of the Electronic Medical Records and Genomics (eMERGE) Network, and one affiliate, in their attempts to implement PGx CDS. We examined the resulting PGx CDS system characteristics and conducted a survey to understand the unanticipated implementation challenges sites encountered. RESULTS Ten sites have successfully implemented at least one PGx CDS rule in the clinical setting. The majority of sites elected to create an Omic Ancillary System (OAS) to manage genetic and genomic data. All sites were able to adapt their existing CDS tools for PGx knowledge. The most common and impactful delays were not PGx-specific issues. Instead, they were general IT implementation problems, with top challenges including team coordination/communication and staffing. The challenges encountered caused a median total delay in system go-live of approximately two months. CONCLUSIONS These results suggest that barriers to PGx CDS implementations are generally surmountable. Moreover, PGx CDS implementation may not be any more difficult than other healthcare IT projects of similar scope, as the most significant delays encountered were not unique to genomic medicine. These are encouraging results for any institution considering implementing a PGx CDS tool, and for the advancement of genomic medicine.
Collapse
Affiliation(s)
- Timothy M Herr
- Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | | | - Erwin Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Ariel Brautbar
- Division of Genetics and Endocrinology, Cook Children's Medical Center, Fort Worth, Texas, USA
| | - Murray Brilliant
- Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - Christopher G Chute
- Division of General Internal Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Beth L Cobb
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University, Baltimore, MD, USA
| | - Hakon Hakonarson
- Department of Pediatrics, The Children's Hospital of Philadelphia, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | | | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Medical Center, New York, USA
| | - Joseph Kannry
- Icahn School of Medicine, Mount Sinai, New York, USA
| | - Isaac S Kohane
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Iftikhar J Kullo
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Simon Lin
- Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Shannon Manzi
- Department of Pharmacy, Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Keith Marsolo
- Department of Pediatrics, University of Cincinnati College of Medicine, Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | | | - Jyotishman Pathak
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Peggy Peissig
- Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - Jill Pulley
- Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - James Ralston
- Group Health Research Institute, Seattle, Washington, USA
| | - Luke Rasmussen
- Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Dan M Roden
- Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Gerard Tromp
- Weis Center for Research, Geisinger Clinic, Danville, Pennsylvania, USA
| | - Timothy Uphoff
- Molecular Pathology, Mashfield Labs, Marshfield, Wisconsin, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, USA
| | - Wendy Wolf
- Department of Pediatrics, Harvard Medical School, Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA
| | - Justin Starren
- Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| |
Collapse
|
33
|
Zawati MH, Junker A, Knoppers BM, Rahimzadeh V. Streamlining review of research involving humans: Canadian models. J Med Genet 2015; 52:566-9. [PMID: 26041760 DOI: 10.1136/jmedgenet-2014-102640] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 05/10/2015] [Indexed: 11/03/2022]
Affiliation(s)
- Ma'n H Zawati
- Faculty of Medicine, Department of Human Genetics, Centre of Genomics and Policy, McGill University, Montreal, Quebec, Canada
| | - Anne Junker
- Faculty of Medicine, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Bartha Maria Knoppers
- Faculty of Medicine, Department of Human Genetics, Centre of Genomics and Policy, McGill University, Montreal, Quebec, Canada
| | - Vasiliki Rahimzadeh
- Faculty of Medicine, Department of Human Genetics, Centre of Genomics and Policy, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
34
|
Kaye J. The Tension Between Data Sharing and the Protection of Privacy in Genomics Research. ETHICS, LAW AND GOVERNANCE OF BIOBANKING 2015. [DOI: 10.1007/978-94-017-9573-9_8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
|
35
|
Budin-Ljøsne I, Burton P, Isaeva J, Gaye A, Turner A, Murtagh MJ, Wallace S, Ferretti V, Harris JR. DataSHIELD: an ethically robust solution to multiple-site individual-level data analysis. Public Health Genomics 2014; 18:87-96. [PMID: 25532061 DOI: 10.1159/000368959] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 10/08/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND DataSHIELD (Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual levEL Databases) has been proposed to facilitate the co-analysis of individual-level data from multiple studies without physically sharing the data. In a previous paper, we investigated whether DataSHIELD could protect participant confidentiality in accordance with UK law. In this follow-up paper, we investigate whether DataSHIELD addresses a broader range of ethics-related data-sharing concerns. METHODS Ethics-related data-sharing concerns of Institutional Review Boards, ethics experts, international research consortia and research participants were identified through a literature search and systematically examined at a multidisciplinary workshop to determine whether DataSHIELD proposes mechanisms which can address these concerns. RESULTS DataSHIELD addresses several ethics-related data-sharing concerns related to privacy, confidentiality, and the protection of the research participant's rights while sharing data and after the data have been shared. The data remain entirely under the direct management of the study that collected them. Data processing commands are strictly supervised, and the data are queried in a protected environment. Issues related to the return of individual research results when data are shared are eliminated; the responsibility for return remains at the study of origin. CONCLUSION DataSHIELD can provide an innovative and robust solution for addressing commonly encountered ethics-related data-sharing concerns.
Collapse
Affiliation(s)
- Isabelle Budin-Ljøsne
- Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway
| | | | | | | | | | | | | | | | | |
Collapse
|
36
|
Brothers KB, Lynch JA, Aufox SA, Connolly JJ, Gelb BD, Holm IA, Sanderson SC, McCormick JB, Williams JL, Wolf WA, Antommaria AHM, Clayton EW. Practical guidance on informed consent for pediatric participants in a biorepository. Mayo Clin Proc 2014; 89:1471-80. [PMID: 25264176 PMCID: PMC4254313 DOI: 10.1016/j.mayocp.2014.07.006] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2014] [Revised: 07/08/2014] [Accepted: 07/10/2014] [Indexed: 12/24/2022]
Affiliation(s)
- Kyle B Brothers
- Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY.
| | - John A Lynch
- Department of Communication, University of Cincinnati, Cincinnati, OH
| | - Sharon A Aufox
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - John J Connolly
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Bruce D Gelb
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ingrid A Holm
- Division of Genetics and Genomics and The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Harvard Medical School, Boston, MA
| | - Saskia C Sanderson
- Department of Genetic and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer B McCormick
- Divisions of General Internal Medicine and Health Care and Policy Research and the Mayo Biomedical Ethics Program, Mayo Clinic, Rochester, MN
| | - Janet L Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, PA
| | - Wendy A Wolf
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA
| | | | - Ellen W Clayton
- Center for Biomedical Ethics and Society, Vanderbilt University Medical Center, Nashville, TN
| |
Collapse
|
37
|
Heitmueller A, Henderson S, Warburton W, Elmagarmid A, Pentland A“S, Darzi A. Developing Public Policy To Advance The Use Of Big Data In Health Care. Health Aff (Millwood) 2014; 33:1523-30. [DOI: 10.1377/hlthaff.2014.0771] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Axel Heitmueller
- Axel Heitmueller ( ) is policy fellow of the Big Data and Health Forum at the World Innovation for Summit for Health (WISH), Qatar Foundation, and an honorary fellow at the Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, in the United Kingdom
| | - Sarah Henderson
- Sarah Henderson is head of forum development at WISH and a policy fellow at the Institute of Global Health Innovation, Imperial College London
| | - Will Warburton
- Will Warburton is forum director at WISH and a senior policy fellow at the Centre for Health Policy, Institute of Global Health Innovation, Imperial College London
| | - Ahmed Elmagarmid
- Ahmed Elmagarmid is executive director of the Qatar Computing Research Institute, Qatar Foundation, in Doha
| | - Alex “Sandy” Pentland
- Alex “Sandy” Pentland is chair of the Big Data and Health Forum for WISH and director of the Human Dynamics Laboratory, Massachusetts Institute of Technology, in Cambridge, Massachusetts
| | - Ara Darzi
- Ara Darzi is executive chair of WISH, Qatar Foundation, and director of the Institute of Global Health Innovation, Imperial College London
| |
Collapse
|
38
|
Knoppers BM, Harris JR, Budin-Ljøsne I, Dove ES. A human rights approach to an international code of conduct for genomic and clinical data sharing. Hum Genet 2014; 133:895-903. [PMID: 24573176 PMCID: PMC4053599 DOI: 10.1007/s00439-014-1432-6] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Accepted: 02/16/2014] [Indexed: 11/30/2022]
Abstract
Fostering data sharing is a scientific and ethical imperative. Health gains can be achieved more comprehensively and quickly by combining large, information-rich datasets from across conventionally siloed disciplines and geographic areas. While collaboration for data sharing is increasingly embraced by policymakers and the international biomedical community, we lack a common ethical and legal framework to connect regulators, funders, consortia, and research projects so as to facilitate genomic and clinical data linkage, global science collaboration, and responsible research conduct. Governance tools can be used to responsibly steer the sharing of data for proper stewardship of research discovery, genomics research resources, and their clinical applications. In this article, we propose that an international code of conduct be designed to enable global genomic and clinical data sharing for biomedical research. To give this proposed code universal application and accountability, however, we propose to position it within a human rights framework. This proposition is not without precedent: international treaties have long recognized that everyone has a right to the benefits of scientific progress and its applications, and a right to the protection of the moral and material interests resulting from scientific productions. It is time to apply these twin rights to internationally collaborative genomic and clinical data sharing.
Collapse
Affiliation(s)
- Bartha M. Knoppers
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal, H3A 0G1 Canada
| | - Jennifer R. Harris
- Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, PO Box 4404, Nydalen, 0403 Oslo Norway
| | - Isabelle Budin-Ljøsne
- Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, PO Box 4404, Nydalen, 0403 Oslo Norway
| | - Edward S. Dove
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal, H3A 0G1 Canada
| |
Collapse
|
39
|
Choudhury S, Fishman JR, McGowan ML, Juengst ET. Big data, open science and the brain: lessons learned from genomics. Front Hum Neurosci 2014; 8:239. [PMID: 24904347 PMCID: PMC4032989 DOI: 10.3389/fnhum.2014.00239] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2014] [Accepted: 04/02/2014] [Indexed: 12/14/2022] Open
Abstract
The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (1024). The scale, investment and organization of it are being compared to the Human Genome Project (HGP), which has exemplified “big science” for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behavior and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this “data driven” paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new “open neuroscience” projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of) motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent “open neuroscience” movement.
Collapse
Affiliation(s)
- Suparna Choudhury
- Division of Social and Transcultural Psychiatry, McGill University and Lady Davis Institute, Jewish General Hospital Montreal, QC, Canada
| | - Jennifer R Fishman
- Biomedical Ethics Unit, Social Studies of Medicine Department, McGill University Montreal, QC, Canada
| | - Michelle L McGowan
- Department of Bioethics, Case Western Reserve University School of Medicine Cleveland, Ohio, USA
| | - Eric T Juengst
- Center for Bioethics, University of North Carolina Chapel Hill, NC, USA
| |
Collapse
|
40
|
Sarwate AD, Plis SM, Turner JA, Arbabshirani MR, Calhoun VD. Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation. Front Neuroinform 2014; 8:35. [PMID: 24778614 PMCID: PMC3985022 DOI: 10.3389/fninf.2014.00035] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 03/19/2014] [Indexed: 11/16/2022] Open
Abstract
The growth of data sharing initiatives for neuroimaging and genomics represents an exciting opportunity to confront the “small N” problem that plagues contemporary neuroimaging studies while further understanding the role genetic markers play in the function of the brain. When it is possible, open data sharing provides the most benefits. However, some data cannot be shared at all due to privacy concerns and/or risk of re-identification. Sharing other data sets is hampered by the proliferation of complex data use agreements (DUAs) which preclude truly automated data mining. These DUAs arise because of concerns about the privacy and confidentiality for subjects; though many do permit direct access to data, they often require a cumbersome approval process that can take months. An alternative approach is to only share data derivatives such as statistical summaries—the challenges here are to reformulate computational methods to quantify the privacy risks associated with sharing the results of those computations. For example, a derived map of gray matter is often as identifiable as a fingerprint. Thus alternative approaches to accessing data are needed. This paper reviews the relevant literature on differential privacy, a framework for measuring and tracking privacy loss in these settings, and demonstrates the feasibility of using this framework to calculate statistics on data distributed at many sites while still providing privacy.
Collapse
Affiliation(s)
- Anand D Sarwate
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey Piscataway, NJ, USA
| | | | - Jessica A Turner
- Mind Research Network Albuquerque, NM, USA ; Department of Psychology and Neuroscience Institute, Georgia State University Atlanta, GA, USA
| | - Mohammad R Arbabshirani
- Mind Research Network Albuquerque, NM, USA ; Department of Electrical and Computer Engineering, University of New Mexico Albuquerque, NM, USA
| | - Vince D Calhoun
- Mind Research Network Albuquerque, NM, USA ; Department of Electrical and Computer Engineering, University of New Mexico Albuquerque, NM, USA
| |
Collapse
|
41
|
Nyholt DR. SECA: SNP effect concordance analysis using genome-wide association summary results. ACTA ACUST UNITED AC 2014; 30:2086-8. [PMID: 24695403 DOI: 10.1093/bioinformatics/btu171] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
UNLABELLED The genomics era provides opportunities to assess the genetic overlap across phenotypes at the measured genotype level; however, current approaches require individual-level genome-wide association (GWA) single nucleotide polymorphism (SNP) genotype data in one or both of a pair of GWA samples. To facilitate the discovery of pleiotropic effects and examine genetic overlap across two phenotypes, I have developed a user-friendly web-based application called SECA to perform SNP effect concordance analysis using GWA summary results. The method is validated using publicly available summary data from the Psychiatric Genomics Consortium. AVAILABILITY AND IMPLEMENTATION http://neurogenetics.qimrberghofer.edu.au/SECA.
Collapse
Affiliation(s)
- Dale R Nyholt
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane 4000, Queensland, Australia
| |
Collapse
|
42
|
Secondary use of clinical data: the Vanderbilt approach. J Biomed Inform 2014; 52:28-35. [PMID: 24534443 DOI: 10.1016/j.jbi.2014.02.003] [Citation(s) in RCA: 174] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2013] [Revised: 12/21/2013] [Accepted: 02/04/2014] [Indexed: 01/04/2023]
Abstract
The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure.
Collapse
|
43
|
Ury AG. Storing and interpreting genomic information in widely deployed electronic health record systems. Genet Med 2013; 15:779-85. [DOI: 10.1038/gim.2013.111] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2013] [Accepted: 06/24/2013] [Indexed: 01/19/2023] Open
|
44
|
Data sharing in large research consortia: experiences and recommendations from ENGAGE. Eur J Hum Genet 2013; 22:317-21. [PMID: 23778872 PMCID: PMC3925260 DOI: 10.1038/ejhg.2013.131] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2013] [Accepted: 05/11/2013] [Indexed: 11/24/2022] Open
Abstract
Data sharing is essential for the conduct of cutting-edge research and is increasingly required by funders concerned with maximising the scientific yield from research data collections. International research consortia are encouraged to share data intra-consortia, inter-consortia and with the wider scientific community. Little is reported regarding the factors that hinder or facilitate data sharing in these different situations. This paper provides results from a survey conducted in the European Network for Genetic and Genomic Epidemiology (ENGAGE) that collected information from its participating institutions about their data-sharing experiences. The questionnaire queried about potential hurdles to data sharing, concerns about data sharing, lessons learned and recommendations for future collaborations. Overall, the survey results reveal that data sharing functioned well in ENGAGE and highlight areas that posed the most frequent hurdles for data sharing. Further challenges arise for international data sharing beyond the consortium. These challenges are described and steps to help address these are outlined.
Collapse
|
45
|
Shoenbill K, Fost N, Tachinardi U, Mendonca EA. Genetic data and electronic health records: a discussion of ethical, logistical and technological considerations. J Am Med Inform Assoc 2013; 21:171-80. [PMID: 23771953 PMCID: PMC3912723 DOI: 10.1136/amiajnl-2013-001694] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Objective The completion of sequencing the human genome in 2003 has spurred the production and collection of genetic data at ever increasing rates. Genetic data obtained for clinical purposes, as is true for all results of clinical tests, are expected to be included in patients’ medical records. With this explosion of information, questions of what, when, where and how to incorporate genetic data into electronic health records (EHRs) have reached a critical point. In order to answer these questions fully, this paper addresses the ethical, logistical and technological issues involved in incorporating these data into EHRs. Materials and methods This paper reviews journal articles, government documents and websites relevant to the ethics, genetics and informatics domains as they pertain to EHRs. Results and discussion The authors explore concerns and tasks facing health information technology (HIT) developers at the intersection of ethics, genetics, and technology as applied to EHR development. Conclusions By ensuring the efficient and effective incorporation of genetic data into EHRs, HIT developers will play a key role in facilitating the delivery of personalized medicine.
Collapse
Affiliation(s)
- Kimberly Shoenbill
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA
| | | | | | | |
Collapse
|
46
|
Gottesman O, Kuivaniemi H, Tromp G, Faucett WA, Li R, Manolio TA, Sanderson SC, Kannry J, Zinberg R, Basford MA, Brilliant M, Carey DJ, Chisholm RL, Chute CG, Connolly JJ, Crosslin D, Denny JC, Gallego CJ, Haines JL, Hakonarson H, Harley J, Jarvik GP, Kohane I, Kullo IJ, Larson EB, McCarty C, Ritchie MD, Roden DM, Smith ME, Böttinger EP, Williams MS. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genet Med 2013; 15:761-71. [PMID: 23743551 PMCID: PMC3795928 DOI: 10.1038/gim.2013.72] [Citation(s) in RCA: 510] [Impact Index Per Article: 46.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2013] [Accepted: 04/18/2013] [Indexed: 12/13/2022] Open
Abstract
The Electronic Medical Records and Genomics Network is a National Human Genome Research Institute–funded consortium engaged in the development of methods and best practices for using the electronic medical record as a tool for genomic research. Now in its sixth year and second funding cycle, and comprising nine research groups and a coordinating center, the network has played a major role in validating the concept that clinical data derived from electronic medical records can be used successfully for genomic research. Current work is advancing knowledge in multiple disciplines at the intersection of genomics and health-care informatics, particularly for electronic phenotyping, genome-wide association studies, genomic medicine implementation, and the ethical and regulatory issues associated with genomics research and returning results to study participants. Here, we describe the evolution, accomplishments, opportunities, and challenges of the network from its inception as a five-group consortium focused on genotype–phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting toward the implementation of genomic medicine. Genet Med15 10, 761–771.
Collapse
|
47
|
McEwen JE, Boyer JT, Sun KY. Evolving approaches to the ethical management of genomic data. Trends Genet 2013; 29:375-82. [PMID: 23453621 PMCID: PMC3665610 DOI: 10.1016/j.tig.2013.02.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2012] [Revised: 01/22/2013] [Accepted: 02/05/2013] [Indexed: 10/27/2022]
Abstract
The ethical landscape in the field of genomics is rapidly shifting. Plummeting sequencing costs, along with ongoing advances in bioinformatics, now make it possible to generate an enormous volume of genomic data about vast numbers of people. The informational richness, complexity, and frequently uncertain meaning of these data, coupled with evolving norms surrounding the sharing of data and samples and persistent privacy concerns, have generated a range of approaches to the ethical management of genomic information. As calls increase for the expanded use of broad or even open consent, and as controversy grows about how best to handle incidental genomic findings, these approaches, informed by normative analysis and empirical data, will continue to evolve alongside the science.
Collapse
Affiliation(s)
- Jean E McEwen
- Ethical, Legal, and Social Implications Program, Division of Genomics and Society, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-9305, USA.
| | | | | |
Collapse
|
48
|
Ramos EM, Din-Lovinescu C, Bookman EB, McNeil LJ, Baker CC, Godynskiy G, Harris EL, Lehner T, McKeon C, Moss J, Starks VL, Sherry ST, Manolio TA, Rodriguez LL. A mechanism for controlled access to GWAS data: experience of the GAIN Data Access Committee. Am J Hum Genet 2013; 92:479-88. [PMID: 23561843 PMCID: PMC3617375 DOI: 10.1016/j.ajhg.2012.08.034] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2012] [Revised: 08/06/2012] [Accepted: 08/06/2012] [Indexed: 11/29/2022] Open
Abstract
The Genetic Association Information Network (GAIN) Data Access Committee was established in June 2007 to provide prompt and fair access to data from six genome-wide association studies through the database of Genotypes and Phenotypes (dbGaP). Of 945 project requests received through 2011, 749 (79%) have been approved; median receipt-to-approval time decreased from 14 days in 2007 to 8 days in 2011. Over half (54%) of the proposed research uses were for GAIN-specific phenotypes; other uses were for method development (26%) and adding controls to other studies (17%). Eight data-management incidents, defined as compromises of any of the data-use conditions, occurred among nine approved users; most were procedural violations, and none violated participant confidentiality. Over 5 years of experience with GAIN data access has demonstrated substantial use of GAIN data by investigators from academic, nonprofit, and for-profit institutions with relatively few and contained policy violations. The availability of GAIN data has allowed for advances in both the understanding of the genetic underpinnings of mental-health disorders, diabetes, and psoriasis and the development and refinement of statistical methods for identifying genetic and environmental factors related to complex common diseases.
Collapse
Affiliation(s)
- Erin M Ramos
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
49
|
Abstract
The number of biobanks around the world has increased dramatically, owing in part, to the need for researchers to have access to large numbers of samples for genomic research. Policies for enrolling participants, returning research results and obtaining samples and data can have a far reaching impact on the type of research that can be performed with each biobank. Research using biobank samples includes studies of the impact of environmental and other risk exposures on health, understanding genetic risks for common disease, identification of biomarkers in disease progression and prognosis, and implementation of personalized medicine projects. This research has been instrumental in the progress of genetic and genomic research and translational medicine. This article will highlight some of the controversies and recent research associated with biobanking over the past year.
Collapse
|
50
|
Fernandez CV, Strahlendorf C, Avard D, Knoppers BM, O'Connell C, Bouffet E, Malkin D, Jabado N, Boycott K, Sorensen PH. Attitudes of Canadian researchers toward the return to participants of incidental and targeted genomic findings obtained in a pediatric research setting. Genet Med 2013; 15:558-64. [PMID: 23370450 PMCID: PMC3910293 DOI: 10.1038/gim.2012.183] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2012] [Accepted: 12/14/2012] [Indexed: 11/23/2022] Open
Abstract
Purpose: The purpose of this study was to explore the attitudes of genomics researchers in a pediatric setting in the context of regulatory guidance recommending the disclosure of clinically significant research findings. Methods: A validated 32-item questionnaire was sent to 107 researchers with two large-scale projects (the Canadian Pediatric Cancer Genome Consortium and the Finding of Rare Genes Canada Consortium). We examined researchers' attitudes toward obligations to offer genomic research results (including if the participant was deceased, a relative, or a child), influence of the certainty/severity of the condition on this obligation, and personal experiences. Results: Of the 107 researchers, 74 (69%) responded. Researchers did not feel a strong responsibility to look for meaningful incidental results in the research genomic data set (n = 27, 37%). However, once identified, they felt participants had a strong right to receive them, irrespective of being incidental (n = 50, 68%) or primary targets (n = 64, 87%). There was a high degree of support for informing siblings of genomic results (n = 46, 62%), especially for treatable conditions (n = 56, 76%). Less than half of the participants indicated that their research ethics board required an offer of results (n = 34, 46%) or provided a detailed process (n = 16, 22%). Conclusion: Researchers strongly support the offer of targeted and incidental genomic research results to participants. Greater regulatory guidance is needed for a consistent approach.
Collapse
Affiliation(s)
- Conrad V Fernandez
- Department of Pediatrics, IWK Health Centre and Dalhousie University, Halifax, Nova Scotia, Canada.
| | | | | | | | | | | | | | | | | | | |
Collapse
|