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Baines R, Stevens S, Austin D, Anil K, Bradwell H, Cooper L, Maramba ID, Chatterjee A, Leigh S. Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review. J Med Internet Res 2024; 26:e50421. [PMID: 38441944 PMCID: PMC10951832 DOI: 10.2196/50421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/01/2023] [Accepted: 12/18/2023] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND International advances in information communication, eHealth, and other digital health technologies have led to significant expansions in the collection and analysis of personal health data. However, following a series of high-profile data sharing scandals and the emergence of COVID-19, critical exploration of public willingness to share personal health data remains limited, particularly for third-party or secondary uses. OBJECTIVE This systematic review aims to explore factors that affect public willingness to share personal health data for third-party or secondary uses. METHODS A systematic search of 6 databases (MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and SocINDEX) was conducted with review findings analyzed using inductive-thematic analysis and synthesized using a narrative approach. RESULTS Of the 13,949 papers identified, 135 were included. Factors most commonly identified as a barrier to data sharing from a public perspective included data privacy, security, and management concerns. Other factors found to influence willingness to share personal health data included the type of data being collected (ie, perceived sensitivity); the type of user requesting their data to be shared, including their perceived motivation, profit prioritization, and ability to directly impact patient care; trust in the data user, as well as in associated processes, often established through individual choice and control over what data are shared with whom, when, and for how long, supported by appropriate models of dynamic consent; the presence of a feedback loop; and clearly articulated benefits or issue relevance including valued incentivization and compensation at both an individual and collective or societal level. CONCLUSIONS There is general, yet conditional public support for sharing personal health data for third-party or secondary use. Clarity, transparency, and individual control over who has access to what data, when, and for how long are widely regarded as essential prerequisites for public data sharing support. Individual levels of control and choice need to operate within the auspices of assured data privacy and security processes, underpinned by dynamic and responsive models of consent that prioritize individual or collective benefits over and above commercial gain. Failure to understand, design, and refine data sharing approaches in response to changeable patient preferences will only jeopardize the tangible benefits of data sharing practices being fully realized.
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Affiliation(s)
- Rebecca Baines
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Sebastian Stevens
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
- Prometheus Health Technologies Ltd, Newquay, United Kingdom
| | - Daniela Austin
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | | | - Hannah Bradwell
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Leonie Cooper
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | | | - Arunangsu Chatterjee
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
- School of Medicine, University of Leeds, Leeds, United Kingdom
| | - Simon Leigh
- Prometheus Health Technologies Ltd, Newquay, United Kingdom
- Warwick Medical School, University of Warwick, Conventry, United Kingdom
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2
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Cervera de la Cruz P, Shabani M. Conceptualizing fairness in the secondary use of health data for research: A scoping review. Account Res 2023:1-30. [PMID: 37851101 DOI: 10.1080/08989621.2023.2271394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/12/2023] [Indexed: 10/19/2023]
Abstract
With the introduction of the European Health Data Space (EHDS), the secondary use of health data for research purposes is attracting more attention. Secondary health data processing promises to address novel research questions, inform the design of future research and improve healthcare delivery generally. To comply with the existing data protection regulations, the secondary data use must be fair, among other things. However, there is no clear understanding of what fairness means in the context of secondary use of health data for scientific research purposes. In response, we conducted a scoping review of argument-based literature to explore how fairness in the secondary use of health data has been conceptualized. A total of 35 publications were included in the final synthesis after abstract and full-text screening. Using an inductive approach and a thematic analysis, our review has revealed that balancing individual and public interests, reducing power asymmetries, setting conditions for commercial involvement, and implementing benefit sharing are essential to guarantee fair secondary use research. The findings of this review can inform current and future research practices and policy development to adequately address concerns about fairness in the secondary use of health data.
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Affiliation(s)
| | - Mahsa Shabani
- Metamedica, Faculty of Law and Criminology, University of Ghent, Ghent, Belgium
- Law Centre for Health and Life, Faculty of Law, University of Amsterdam, Amsterdam, The Netherlands
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3
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O’Sullivan KK, Wilde KJ. A profile of the Grampian Data Safe Haven, a regional Scottish safe haven for health and population data research. Int J Popul Data Sci 2023; 4:1817. [PMID: 37671386 PMCID: PMC10476148 DOI: 10.23889/ijpds.v4i2.1817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
There has been a recent emphasis to establish and codify large-scale or national Trusted Research Environments (TREs) in the United Kingdom, with a view to limit smaller, local TREs. The basis for this argument is that it avoids duplication of infrastructure, information governance, privacy risks, monopolies and will promote innovation, particularly with commercial partners. However, the work around establishing TREs in the UK largely ignores the long-established local TRE landscape in Scotland, and the way in which local TREs can actually improve data quality, solve technical architecture challenges, promote information governance and risk minimisation, and encourage innovation and collaboration (both academic and commercial). This data centre profile focuses on the Grampian Data Safe Haven (DaSH), a secure, virtual healthcare data analysis and storage centre located in Aberdeen, Scotland. DaSH was co-established by the NHS Grampian Health Board and University of Aberdeen to allow for the secure processing and linking of health data for the Grampian and Scottish population when it is not practicable to obtain consent from individual patients. As an established trusted research environment now in its 10th operating year, DaSH technology ensures healthcare, social care data and other types of sensitive data, routinely collected and used without individual patient consent, are made accessible for both academic research and clinical service evaluation and improvements whilst protecting individuals' privacy at the local, national and international levels. DaSH has registered almost 600 projects and facilitated over 200 distinct research projects with data hosting, extraction, and novel linkages to completion. Ongoing innovation and collaboration between DaSH and the NHS Grampian Health Board continues to expand researcher access to new types of data and data linkages, introduce new technologies for advanced statistical research methods, and supports interdisciplinary research using population health and social care data for research, clinical and commercial advancements, and real-world practitioner applications. The purpose of this paper is to present DaSH's data population, operating model, architecture and information technology, governance, legislation and management, privacy-by-design principles and data access, data linkage methods, data sources, noteworthy research outputs, and further developments in order to demonstrate the value of local TREs within the data management and access debate.
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Affiliation(s)
| | - Katie J. Wilde
- Grampian DaSH, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD
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4
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Cumyn A, Ménard JF, Barton A, Dault R, Lévesque F, Ethier JF. Patients and Members of the Public’s Wishes Regarding Transparency in the Context of Secondary Use of Health Data: A Scoping Review (Preprint). J Med Internet Res 2022; 25:e45002. [PMID: 37052967 PMCID: PMC10141314 DOI: 10.2196/45002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/09/2023] [Accepted: 03/03/2023] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness. OBJECTIVE We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations. METHODS Using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using Medline, CINAHL, PsycINFO, Scopus, Cochrane Library, and PubMed databases to locate a broad range of studies published in English or French until November 2022. We included articles reporting a stakeholder's perspective or recommendations of what information patients and members of the public want to learn about the secondary use of health data for research purposes and how or in which situations. Data were collected and analyzed with an iterative thematic approach using NVivo. RESULTS Overall, 178 articles were included in this scoping review. The type of information can be divided into generic and specific content. Generic content includes information on governance and regulatory frameworks, technical aspects, and scientific aims. Specific content includes updates on the use of one's data, return of results from individual tests, information on global results, information on data sharing, and how to access one's data. Recommendations on how to communicate the information focused on frequency, use of various supports, formats, and wording. Methods for communication generally favored broad approaches such as nationwide publicity campaigns, mainstream and social media for generic content, and mixed approaches for specific content including websites, patient portals, and face-to-face encounters. Content should be tailored to the individual as much as possible with regard to length, avoidance of technical terms, cultural competence, and level of detail. Finally, the review outlined 4 major situations where communication was deemed necessary: before a new use of data, when new test results became available, when global research results were released, and in the advent of a breach in confidentiality. CONCLUSIONS This review highlights how different types of information and approaches to communication efforts may serve as the basis for achieving greater transparency. Governing bodies could use the results: to elaborate or evaluate strategies to educate on the potential benefits; to provide some knowledge and control over data use as a form of reciprocity; and as a condition to engage citizens and build and maintain trust. Future work is needed to assess which strategies achieve the greatest outreach while striking a balance between meeting information needs and use of resources.
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Affiliation(s)
- Annabelle Cumyn
- Département de médecine, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-Frédéric Ménard
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Faculté de droit, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Adrien Barton
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Institut de recherche en informatique de Toulouse, Toulouse, France
| | - Roxanne Dault
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Frédérique Lévesque
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-François Ethier
- Département de médecine, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
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5
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Shiells K, Di Cara N, Skatova A, Davis OS, Haworth CM, Skinner AL, Thomas R, Tanner AR, Macleod J, Timpson NJ, Boyd A. Participant acceptability of digital footprint data collection strategies: an exemplar approach to participant engagement and involvement in the ALSPAC birth cohort study. Int J Popul Data Sci 2022; 5:1728. [PMID: 35519823 PMCID: PMC9053133 DOI: 10.23889/ijpds.v7i1.1728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Introduction Digital footprint records - the tracks and traces amassed by individuals as a result of their interactions with the internet, digital devices and services - can provide ecologically valid data on individual behaviours. These could enhance longitudinal population study databanks; but few UK longitudinal studies are attempting this. When using novel sources of data, study managers must engage with participants in order to develop ethical data processing frameworks that facilitate data sharing whilst safeguarding participant interests. Objectives This paper aims to summarise the participant involvement approach used by the ALSPAC birth cohort study to inform the development of a framework for using linked participant digital footprint data, and provide an exemplar for other data linkage infrastructures. Methods The paper synthesises five qualitative forms of inquiry. Thematic analysis was used to code transcripts for common themes in relation to conditions associated with the acceptability of sharing digital footprint data for longitudinal research. Results We identified six themes: participant understanding; sensitivity of location data; concerns for third parties; clarity on data granularity; mechanisms of data sharing and consent; and trustworthiness of the organisation. For cohort members to consider the sharing of digital footprint data acceptable, they require information about the value, validity and risks; control over sharing elements of the data they consider sensitive; appropriate mechanisms to authorise or object to their records being used; and trust in the organisation. Conclusion Realising the potential for using digital footprint records within longitudinal research will be subject to ensuring that this use of personal data is acceptable; and that rigorously controlled population data science benefiting the public good is distinguishable from the misuse and lack of personal control of similar data within other settings. Participant co-development informs the ethical-governance framework for these novel linkages in a manner which is acceptable and does not undermine the role of the trusted data custodian.
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Affiliation(s)
- Kate Shiells
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Alan Turing Institute, London, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nina Di Cara
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Anya Skatova
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Alan Turing Institute, London, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Oliver S.P. Davis
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Claire M.A. Haworth
- Alan Turing Institute, London, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Andy L. Skinner
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Integrative Cancer Epidemiology Programme, University of Bristol, Bristol, UK
| | - Richard Thomas
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Alastair R. Tanner
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - John Macleod
- Avon Longitudinal Study of Parents and Children, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West, Bristol, UK
| | - Nicholas J. Timpson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Avon Longitudinal Study of Parents and Children, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andy Boyd
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Avon Longitudinal Study of Parents and Children, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- CLOSER longitudinal study consortium, University College London, London, UK
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6
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Taylor D. AIM and the Patient’s Perspective. Artif Intell Med 2022. [DOI: 10.1007/978-3-030-64573-1_37] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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7
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Cushnan D, Berka R, Bertolli O, Williams P, Schofield D, Joshi I, Favaro A, Halling-Brown M, Imreh G, Jefferson E, Sebire NJ, Reilly G, Rodrigues JCL, Robinson G, Copley S, Malik R, Bloomfield C, Gleeson F, Crotty M, Denton E, Dickson J, Leeming G, Hardwick HE, Baillie K, Openshaw PJ, Semple MG, Rubin C, Howlett A, Rockall AG, Bhayat A, Fascia D, Sudlow C, Jacob J. Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic. Digit Health 2021; 7:20552076211048654. [PMID: 34868617 PMCID: PMC8637703 DOI: 10.1177/20552076211048654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 09/07/2021] [Indexed: 12/27/2022] Open
Abstract
The prevalence of the coronavirus SARS-CoV-2 disease has resulted in the
unprecedented collection of health data to support research. Historically,
coordinating the collation of such datasets on a national scale has been
challenging to execute for several reasons, including issues with data privacy,
the lack of data reporting standards, interoperable technologies, and
distribution methods. The coronavirus SARS-CoV-2 disease pandemic has
highlighted the importance of collaboration between government bodies,
healthcare institutions, academic researchers and commercial companies in
overcoming these issues during times of urgency. The National COVID-19 Chest
Imaging Database, led by NHSX, British Society of Thoracic Imaging, Royal Surrey
NHS Foundation Trust and Faculty, is an example of such a national initiative.
Here, we summarise the experiences and challenges of setting up the National
COVID-19 Chest Imaging Database, and the implications for future ambitions of
national data curation in medical imaging to advance the safe adoption of
artificial intelligence in healthcare.
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Affiliation(s)
| | | | | | | | | | | | | | - Mark Halling-Brown
- Scientific Computing, Royal Surrey NHS Foundation Trust, UK.,CVSSP, University of Surrey, UK
| | | | - Emily Jefferson
- Health Data Research UK, UK.,Health Informatics Centre (HIC), School of Medicine, University of Dundee, UK
| | | | | | | | - Graham Robinson
- Department of Radiology, Royal United Hospitals Bath NHS Foundation Trust, UK
| | - Susan Copley
- Imaging Department, Hammersmith Hospital, Imperial College NHS Healthcare Trust, UK
| | - Rizwan Malik
- Department of Radiology, Bolton NHS Foundation Trust, UK
| | - Claire Bloomfield
- National Consortium of Intelligent Medical Imaging (NCIMI), The Big Data Institute, University of Oxford, UK.,Dept of Oncology, University of Oxford, UK
| | - Fergus Gleeson
- National Consortium of Intelligent Medical Imaging (NCIMI), The Big Data Institute, University of Oxford, UK.,Dept of Oncology, University of Oxford, UK
| | | | - Erika Denton
- Norfolk and Norwich University Hospital Foundation Trust, UK
| | | | - Gary Leeming
- Institute of Population Health, Faculty of Health and Life Sciences, University of Liverpool, UK
| | - Hayley E Hardwick
- National Institute of Health Research (NIHR) Health Protection Research Unit in Emerging and Zoonotic Infections, UK
| | | | | | - Malcolm G Semple
- NIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, UK
| | - Caroline Rubin
- Department of Radiology, University Hospital Southampton NHS Foundation Trust, UK
| | | | - Andrea G Rockall
- Imaging Department, Hammersmith Hospital, Imperial College NHS Healthcare Trust, UK.,Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, UK
| | - Ayub Bhayat
- NHS Arden & Greater East Midlands Commissioning Support Unit, UK
| | | | - Cathie Sudlow
- British Heart Foundation Data Science Centre Led by Health Data Research UK, UK
| | | | - Joseph Jacob
- Department of Respiratory Medicine, University College London, UK.,Centre for Medical Image Computing, Department of Computer Science, University College London, UK
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8
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Kasperbauer TJ, Halverson C, Garcia A, Schwartz PH. Biobank Participants' Attitudes Toward Data Sharing and Privacy: The Role of Trust in Reducing Perceived Risks. J Empir Res Hum Res Ethics 2021; 17:167-176. [PMID: 34779299 DOI: 10.1177/15562646211055282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Biobank participants are often unaware of possible uses of their genetic and health information, despite explicit descriptions of those uses in consent forms. To explore why this misunderstanding persists, we conducted semi-structured interviews and knowledge tests with 22 participants who had recently enrolled in a research biobank. Results indicated that participants lacked understanding of privacy and data-sharing topics but were mostly unconcerned about associated risks. Participants described their answers on the knowledge test as largely driven by their trust in the healthcare system, not by a close reading of the information presented to them. This finding may help explain the difficulties in increasing participant understanding of privacy-related topics, even when such information is clearly presented in biobank consent forms.
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Affiliation(s)
- T J Kasperbauer
- Indiana University Center for Bioethics, 12250Indiana University School of Medicine, Indianapolis, IN, USA
| | - Colin Halverson
- Indiana University Center for Bioethics, 12250Indiana University School of Medicine, Indianapolis, IN, USA
| | - Abby Garcia
- Indiana University Center for Bioethics, 12250Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter H Schwartz
- Indiana University Center for Bioethics, 12250Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Philosophy, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
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9
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Ellis LA, Sarkies M, Churruca K, Dammery G, Meulenbroeks I, Smith CL, Pomare C, Mahmoud Z, Zurynski Y, Braithwaite J. The science of learning health systems: A scoping review of the empirical research (Preprint). JMIR Med Inform 2021; 10:e34907. [PMID: 35195529 PMCID: PMC8908194 DOI: 10.2196/34907] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/07/2021] [Accepted: 01/02/2022] [Indexed: 01/26/2023] Open
Affiliation(s)
- Louise A Ellis
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Mitchell Sarkies
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Kate Churruca
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Genevieve Dammery
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | | | - Carolynn L Smith
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Chiara Pomare
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Zeyad Mahmoud
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Yvonne Zurynski
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Jeffrey Braithwaite
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
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10
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Wongkoblap A, Vadillo MA, Curcin V. Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study. JMIR Ment Health 2021; 8:e19824. [PMID: 34383688 PMCID: PMC8380581 DOI: 10.2196/19824] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 09/02/2020] [Accepted: 03/31/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Mental health problems are widely recognized as a major public health challenge worldwide. This concern highlights the need to develop effective tools for detecting mental health disorders in the population. Social networks are a promising source of data wherein patients publish rich personal information that can be mined to extract valuable psychological cues; however, these data come with their own set of challenges, such as the need to disambiguate between statements about oneself and third parties. Traditionally, natural language processing techniques for social media have looked at text classifiers and user classification models separately, hence presenting a challenge for researchers who want to combine text sentiment and user sentiment analysis. OBJECTIVE The objective of this study is to develop a predictive model that can detect users with depression from Twitter posts and instantly identify textual content associated with mental health topics. The model can also address the problem of anaphoric resolution and highlight anaphoric interpretations. METHODS We retrieved the data set from Twitter by using a regular expression or stream of real-time tweets comprising 3682 users, of which 1983 self-declared their depression and 1699 declared no depression. Two multiple instance learning models were developed-one with and one without an anaphoric resolution encoder-to identify users with depression and highlight posts related to the mental health of the author. Several previously published models were applied to our data set, and their performance was compared with that of our models. RESULTS The maximum accuracy, F1 score, and area under the curve of our anaphoric resolution model were 92%, 92%, and 90%, respectively. The model outperformed alternative predictive models, which ranged from classical machine learning models to deep learning models. CONCLUSIONS Our model with anaphoric resolution shows promising results when compared with other predictive models and provides valuable insights into textual content that is relevant to the mental health of the tweeter.
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Affiliation(s)
- Akkapon Wongkoblap
- Department of Informatics, King's College London, London, United Kingdom.,DIGITECH, Suranaree University of Technology, Nakhon Ratchasima, Thailand.,School of Information Technology, Suranaree University of Technology, Nakhon Ratchasima, Thailand
| | - Miguel A Vadillo
- School of Population Health and Environmental Sciences, King's College London, London, United Kingdom.,Departamento de Psicología Básica, Universidad Autónoma de Madrid, Madrid, Spain
| | - Vasa Curcin
- Department of Informatics, King's College London, London, United Kingdom.,School of Population Health and Environmental Sciences, King's College London, London, United Kingdom
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11
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Street J, Fabrianesi B, Adams C, Flack F, Smith M, Carter SM, Lybrand S, Brown A, Joyner S, Mullan J, Lago L, Carolan L, Irvine K, Wales C, Braunack‐Mayer AJ. Sharing administrative health data with private industry: A report on two citizens' juries. Health Expect 2021; 24:1337-1348. [PMID: 34048624 PMCID: PMC8369100 DOI: 10.1111/hex.13268] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 03/15/2021] [Accepted: 04/08/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND There is good evidence of both community support for sharing public sector administrative health data in the public interest and concern about data security, misuse and loss of control over health information, particularly if private sector organizations are the data recipients. To date, there is little research describing the perspectives of informed community members on private sector use of public health data and, particularly, on the conditions under which that use might be justified. METHODS Two citizens' juries were held in February 2020 in two locations close to Sydney, Australia. Jurors considered the charge: 'Under what circumstances is it permissible for governments to share health data with private industry for research and development?' RESULTS All jurors, bar one, in principle supported sharing government administrative health data with private industry for research and development. The support was conditional and the juries' recommendations specifying these conditions related closely to the concerns they identified in deliberation. CONCLUSION The outcomes of the deliberative processes suggest that informed Australian citizens are willing to accept sharing their administrative health data, including with private industry, providing the intended purpose is clearly of public benefit, sharing occurs responsibly in a framework of accountability, and the data are securely held. PATIENT AND PUBLIC CONTRIBUTION The design of the jury was guided by an Advisory Group including representatives from a health consumer organization. The jurors themselves were selected to be descriptively representative of their communities and with independent facilitation wrote the recommendations.
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Affiliation(s)
- Jackie Street
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and SocietyUniversity of WollongongWollongongNSWAustralia
| | - Belinda Fabrianesi
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and SocietyUniversity of WollongongWollongongNSWAustralia
| | - Carolyn Adams
- Macquarie Law SchoolMacquarie UniversitySydneyNSWAustralia
| | - Felicity Flack
- Population Health Research NetworkUniversity of Western AustraliaPerthWAAustralia
| | - Merran Smith
- Population Health Research NetworkUniversity of Western AustraliaPerthWAAustralia
| | - Stacy M. Carter
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and SocietyUniversity of WollongongWollongongNSWAustralia
| | | | - Anthony Brown
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and SocietyUniversity of WollongongWollongongNSWAustralia
- Health Consumers NSWSydneyNSWAustralia
| | | | - Judy Mullan
- Centre for Health Research Illawarra Shoalhaven PopulationUniversity of WollongongWollongongNSWAustralia
| | - Luise Lago
- Centre for Health Research Illawarra Shoalhaven PopulationUniversity of WollongongWollongongNSWAustralia
| | - Lucy Carolan
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and SocietyUniversity of WollongongWollongongNSWAustralia
| | - Katie Irvine
- The Centre for Health Record LinkageNorth SydneyNSWAustralia
| | - Coralie Wales
- Western Sydney Local Health DistrictNorth ParramattaNSWAustralia
| | - Annette J. Braunack‐Mayer
- Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and SocietyUniversity of WollongongWollongongNSWAustralia
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12
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Hassan L, Nenadic G, Tully MP. A Social Media Campaign (#datasaveslives) to Promote the Benefits of Using Health Data for Research Purposes: Mixed Methods Analysis. J Med Internet Res 2021; 23:e16348. [PMID: 33591280 PMCID: PMC7925154 DOI: 10.2196/16348] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 07/27/2020] [Accepted: 12/07/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Social media provides the potential to engage a wide audience about scientific research, including the public. However, little empirical research exists to guide health scientists regarding what works and how to optimize impact. We examined the social media campaign #datasaveslives established in 2014 to highlight positive examples of the use and reuse of health data in research. OBJECTIVE This study aims to examine how the #datasaveslives hashtag was used on social media, how often, and by whom; thus, we aim to provide insights into the impact of a major social media campaign in the UK health informatics research community and further afield. METHODS We analyzed all publicly available posts (tweets) that included the hashtag #datasaveslives (N=13,895) on the microblogging platform Twitter between September 1, 2016, and August 31, 2017. Using a combination of qualitative and quantitative analyses, we determined the frequency and purpose of tweets. Social network analysis was used to analyze and visualize tweet sharing (retweet) networks among hashtag users. RESULTS Overall, we found 4175 original posts and 9720 retweets featuring #datasaveslives by 3649 unique Twitter users. In total, 66.01% (2756/4175) of the original posts were retweeted at least once. Higher frequencies of tweets were observed during the weeks of prominent policy publications, popular conferences, and public engagement events. Cluster analysis based on retweet relationships revealed an interconnected series of groups of #datasaveslives users in academia, health services and policy, and charities and patient networks. Thematic analysis of tweets showed that #datasaveslives was used for a broader range of purposes than indexing information, including event reporting, encouraging participation and action, and showing personal support for data sharing. CONCLUSIONS This study shows that a hashtag-based social media campaign was effective in encouraging a wide audience of stakeholders to disseminate positive examples of health research. Furthermore, the findings suggest that the campaign supported community building and bridging practices within and between the interdisciplinary sectors related to the field of health data science and encouraged individuals to demonstrate personal support for sharing health data.
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Affiliation(s)
- Lamiece Hassan
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, United Kingdom
| | - Goran Nenadic
- Department of Computer Science, The University of Manchester, Manchester, United Kingdom
| | - Mary Patricia Tully
- Division of Pharmacy and Optometry, The University of Manchester, Manchester, United Kingdom
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13
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Jackson BR, Ye Y, Crawford JM, Becich MJ, Roy S, Botkin JR, de Baca ME, Pantanowitz L. The Ethics of Artificial Intelligence in Pathology and Laboratory Medicine: Principles and Practice. Acad Pathol 2021; 8:2374289521990784. [PMID: 33644301 PMCID: PMC7894680 DOI: 10.1177/2374289521990784] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 11/24/2020] [Accepted: 12/28/2020] [Indexed: 12/24/2022] Open
Abstract
Growing numbers of artificial intelligence applications are being developed and applied to pathology and laboratory medicine. These technologies introduce risks and benefits that must be assessed and managed through the lens of ethics. This article describes how long-standing principles of medical and scientific ethics can be applied to artificial intelligence using examples from pathology and laboratory medicine.
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Affiliation(s)
- Brian R. Jackson
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
- ARUP Laboratories, Salt Lake City, UT, USA
| | - Ye Ye
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - James M. Crawford
- Department of Pathology and Laboratory Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Michael J. Becich
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Somak Roy
- Division of Pathology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Jeffrey R. Botkin
- Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA
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14
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Taylor D. AIM and the Patient’s Perspective. Artif Intell Med 2021. [DOI: 10.1007/978-3-030-58080-3_37-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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15
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Waind E. Trust, security and public interest: striking the balance A narrative review of previous literature on public attitudes towards the sharing, linking and use of administrative data for research. Int J Popul Data Sci 2020; 5:1368. [PMID: 34036179 PMCID: PMC8127133 DOI: 10.23889/ijpds.v5i3.1368] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
This narrative literature review explores previous findings in relation to the UK public’s attitudes towards the sharing, linking and use of public sector administrative data for research. A total of 16 papers are included in the review, for which data was collected between the years 2006-2018. The review finds, on the basis of previous literature on the topic, that the public is broadly supportive of administrative data research if three core conditions are met: public interest, privacy and security, and trust and transparency. None of these conditions is sufficient in isolation; the literature shows public support is underpinned by fulfillment of all three. However, it also shows that in certain cases where the standard of one condition is very high – particularly public interest – this could mean the standard of another may, if necessary, be lower. An appropriate balance must be struck, and the proposed benefits of sharing and using data for research must outweigh the potential risks. Broad, conditional support for the use of administrative data in research has not only been found consistently, but has also been held over time. Most studies identified by this review have focused on exploring the views of the general public towards the acceptability of administrative data use in broad terms. However, with the exception of that related to healthcare data, the review identified little work focused on gaining input from relevant demographics and communities in relation to specific data types or areas of research. In addition to fulfilling the core conditions of public support identified by broader work, initiatives making use of administrative data should aim to seek the views of relevant sub-sectors of the public in the development of research in relation to specific issues.
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Affiliation(s)
- Elizabeth Waind
- Administrative Data Research UK (ADR UK), Economic & Social Research Council (ESRC
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