Patient data and patient rights: Swiss healthcare stakeholders' ethical awareness regarding large patient data sets - a qualitative study

Participatory evaluation of the process of co-producing resources for the public on data science and artificial intelligence

BACKGROUND

The growth of data science and artificial intelligence offers novel healthcare applications and research possibilities. Patients should be able to make informed choices about using healthcare. Therefore, they must be provided with lay information about new technology. A team consisting of academic researchers, health professionals, and public contributors collaboratively co-designed and co-developed the new resource offering that information. In this paper, we evaluate this novel approach to co-production.

METHODS

We used participatory evaluation to understand the co-production process. This consisted of creative approaches and reflexivity over three stages. Firstly, everyone had an opportunity to participate in three online training sessions. The first one focused on the aims of evaluation, the second on photovoice (that included practical training on using photos as metaphors), and the third on being reflective (recognising one's biases and perspectives during analysis). During the second stage, using photovoice, everyone took photos that symbolised their experiences of being involved in the project. This included a session with a professional photographer. At the last stage, we met in person and, using data collected from photovoice, built the mandala as a representation of a joint experience of the project. This stage was supported by professional artists who summarised the mandala in the illustration.

RESULTS

The mandala is the artistic presentation of the findings from the evaluation. It is a shared journey between everyone involved. We divided it into six related layers. Starting from inside layers present the following experiences (1) public contributors had space to build confidence in a new topic, (2) relationships between individuals and within the project, (3) working remotely during the COVID-19 pandemic, (4) motivation that influenced people to become involved in this particular piece of work, (5) requirements that co-production needs to be inclusive and accessible to everyone, (6) expectations towards data science and artificial intelligence that researchers should follow to establish public support.

CONCLUSIONS

The participatory evaluation suggests that co-production around data science and artificial intelligence can be a meaningful process that is co-owned by everyone involved.

Exploring how to improve the involvement of Polish and South Asian communities around big data research. A qualitative study using COM-B model

Introduction

Involving public contributors helps researchers to ensure that public views are taken into consideration when designing and planning research, so that it is person-centred and relevant to the public. This paper will consider public involvement in big data research. Inclusion of different communities is needed to ensure everyone's voice is heard. However, there remains limited evidence on how to improve the involvement of seldom-heard communities in big data research.

Objectives

This study aims to understand how South Asians and Polish communities in the UK can be encouraged to participate in public involvement initiatives in big data research.

Methods

Forty interviews were conducted with Polish (n=20) and South Asian (n=20) participants on Zoom. The participants were living in the United Kingdom and had not previously been involved as public contributors. Transcribed interviews were analysed using reflexive thematic analysis.

Results

We identified eight themes. The 'happy to reuse data' theme sets the scene by exploring our participants' views towards big data research and under what circumstances they thought that data could be used. The remaining themes were mapped under the capability-opportunity-motivation-behaviour (COM-B) model, as developed by Michie and colleagues. This allowed us to discuss multiple factors that could influence people's willingness to become public contributors.

Conclusions

Our study is the first to explore how to improve the involvement and engagement of seldom-heard communities in big data research using the COM-B model. The results have the potential to support researchers who want to identify what can influence members of the public to be involved. By using the COM-B model, it is possible to determine what measures could be implemented to better engage these communities.

Patients' and Members of the Public's Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review

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.

'To me, it's ones and zeros, but in reality that one is death': A qualitative study exploring researchers' experience of involving and engaging seldom-heard communities in big data research

BACKGROUND

Big data research requires public support. It has been argued that this can be achieved by public involvement and engagement to ensure that public views are at the centre of research projects. Researchers should aim to include diverse communities, including seldom-heard voices, to ensure that a range of voices are heard and that research is meaningful to them.

OBJECTIVE

We explored how researchers involve and engage seldom-heard communities around big data research.

METHODS

This is a qualitative study. Researchers who had experience of involving or engaging seldom-heard communities in big data research were recruited. They were based in England (n = 5), Scotland (n = 4), Belgium (n = 2) and Canada (n = 1). Twelve semistructured interviews were conducted on Zoom. All interviews were audio-recorded and transcribed, and we used reflexive thematic analysis to analyse participants' experiences.

RESULTS

The analysis highlighted the complexity of involving and engaging seldom-heard communities around big data research. Four themes were developed to represent participants' experiences: (1) abstraction and complexity of big data, (2) one size does not fit all, (3) working in partnership and (4) empowering the public contribution.

CONCLUSION

The study offers researchers a better understanding of how to involve and engage seldom-heard communities in a meaningful way around big data research. There is no one right approach, with involvement and engagement activities required to be project-specific and dependent on the public contributors, researchers' needs, resources and time available.

PATIENT AND PUBLIC INVOLVEMENT

Two public contributors are authors of the paper and they were involved in the study design, analysis and writing.

Reporting violations of European Charter of Patients' Rights: analysis of patient complaints in Croatia

Background

The European Charter of Patients' Rights (ECPR) presents basic patients' rights in health care. We analysed the characteristics of patients' complaints about their rights submitted through the official complaints system and to a non-governmental organization in Croatia.

Methods

The official system for patients’complaints in Croatia does not have a common pathway but offers different modes for addressing patient complaints. In this cross-sectional study, we analysed the reports about patients’ complaints from the official regional committees sent to the Ministry of Health. We also analysed the complaints received by the Croatian Association for the Protection of Patient’s Rights (CAPR) and mapped them to the ECPR.

Results

The aggregated official data from the Ministry of Health in 2017 and 2018 covered only 289 individual complaints from 10 out of 21 counties. Complaints were most frequently related to secondary and tertiary healthcare institutions and details were not provided. CAPR received a total of 440 letters, out of which 207 contained 301 complaints about violations of patients’ rights in 2017–2018. The most common complaint was the Right of Access to health care (35.3%) from the ECPR, followed by the Right to Information (29.9%) and the Right to Safety (21.7%). The fewest complaints were about the Right to Complain (1.9%), Right to Innovation (1.4%), Right to Compensation (1.4%), and Right to Preventive Measures (1.0%).

Conclusions

Reporting and dealing with patients’ complaints about violations of their patients’ rights does not appear to be effective in a system with parallel but uncoordinated complaints pathways. Mapping patient's complaints to the ECPR is a useful tool to assess the perception of patients’ rights and to plan actions to improve the complaints system for effective health care.

Considerations for an integrated population health databank in Africa: lessons from global best practices

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.

Public involvement and engagement in big data research: protocol for a scoping review and a systematic review of delivery and effectiveness of strategies for involvement and engagement

INTRODUCTION

Big data research has grown considerably over the last two decades. This presents new ethical challenges around consent, data storage and anonymisation. Big data research projects require public support to succeed and it has been argued that one way to achieve this is through public involvement and engagement. To better understand the role public involvement and engagement can play in big data research, we will review the current literature. This protocol describes the planned review methods.

METHODS AND ANALYSIS

Our review will be conducted in two stages. In the first stage, we will conduct a scoping review using Arksey and O'Malley methodology to comprehensively map current evidence on public involvement and engagement in big data research. Databases (CINAHL, Health Research Premium Collection, PubMed, Scopus, Web of Science) and grey literature will be searched for eligible papers. We provide a narrative description of the results based on a thematic analysis. In the second stage, out of papers found in the scoping review which discuss involvement and engagement strategies, we will conduct a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, exploring the delivery and effectiveness of these strategies. We will conduct a qualitative synthesis. Relevant results from the quantitative studies will be extracted and placed under qualitative themes. Individual studies will be appraised through Mixed Methods Appraisal Tool (MMAT), we will then assess the overall confidence in each finding through Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual). Results will be reported in a thematic and narrative way.

ETHICS AND DISSEMINATION

This protocol sets out how the review will be conducted to ensure rigour and transparency. Public advisors were involved in its development. Ethics approval is not required. Review findings will be presented at conferences and published in peer-reviewed journals.

'It’s not something you can take in your hands'. Swiss experts’ perspectives on health data ownership: an interview-based study

Objectives

The evolution of healthcare and biomedical research into data-rich fields has raised several questions concerning data ownership. In this paper, we aimed to analyse the perspectives of Swiss experts on the topic of health data ownership and control.

Design

In our qualitative study, we selected participants through purposive and snowball sampling. Interviews were recorded, transcribed verbatim and then analysed thematically.

Setting

Semi-structured interviews were conducted in person, via phone or online.

Participants

We interviewed 48 experts (researchers, policy makers and other stakeholders) of the Swiss health-data framework.

Results

We identified different themes linked to data ownership. These include: (1) the data owner: data-subjects versus data-processors; (2) uncertainty about data ownership; (3) labour as a justification for data ownership and (4) the market value of data. Our results suggest that experts from Switzerland are still divided about who should be the data owner and also about what ownership would exactly mean. There is ambivalence between the willingness to acknowledge patients as the data owners and the fact that the effort made by data-processors (eg, researchers) to collect and manage the data entitles them to assert ownership claims towards the data themselves. Altogether, a tendency to speak about data in market terms also emerged.

Conclusions

The development of a satisfactory account of data ownership as a concept to organise the relationship between data-subjects, data-processors and data themselves is an important endeavour for Switzerland and other countries who are developing data governance in the healthcare and research domains. Setting clearer rules on who owns data and on what ownership exactly entails would be important. If this proves unfeasible, the idea that health data cannot truly belong to anyone could be promoted. However, this will not be easy, as data are seen as an asset to control and profit from.

Community-based Health Data Cooperatives Towards Improving the Immigrant Community Health: A Scoping Review to Inform Policy and Practice

Background

In the case of immigrant health and wellness, data are the key limiting factor, where comprehensive national knowledge on immigrant health and health service utilisation is limited. New data and data silos are an inherent response to the increase in technology in the collection and storage of data. The Health Data Cooperative (HDC) model allows members to contribute, store, and manage their health-related information, and members are the rightful data owners and decision-makers to data sharing (e g. research communities, commercial entities, government bodies).

Objective

This review attempts to scope the literature on HDC and fulfill the following objectives: 1) identify and describe the type of literature that is available on the HDC model; 2) describe the key themes related to HDCs; and 3) describe the benefits and challenges related to the HDC model.

Methods

We conducted a scoping review using the five-stage framework outlined by Arskey and O’Malley to systematically map literature on HDCs using two search streams: 1) a database and grey literature search; and 2) an internet search. We included all English records that discussed health data cooperative and related key terms. We used a thematic analysis to collate information into comprehensive themes.

Results

Through a comprehensive screening process, we found 22 database and grey literature records, and 13 Internet search records. Three major themes that are important to stakeholders include data ownership, data security, and data flow and infrastructure.

Conclusions

The results of this study are an informative first step to the study of the HDC model, or an establishment of a HDC in immigrant communities.

Key words

community health, health data, cooperative, and citizen data empowermen

Public Attitudes Toward Precision Medicine: A Nationwide Survey on Developing a National Cohort Program for Citizen Participation in the Republic of Korea

This nation-wide survey was conducted among Korean adults to examine the public interest in and attitudes toward establishing a citizen participation cohort model and to collect data to support and determine the future policy and research directions of the Resource Collection Project for Precision Medicine Research (RCP-PMR) before the project proceeds. The demographic framework of the survey population was established based on the statistical standards of the Ministry of the Interior and Safety. An online survey was carried out using web panels between 14 May 2018 and 23 May 2018. Sampling was performed using a simple proportional allocation method considering region, gender, and age. From this survey, the RCP-PMR received very high support (94.5%) and the intention to participate was as high as 83.5%. Respondents had a very positive attitude toward providing their samples and information to the study (84.5-89.9%). In terms of incentives to participate, respondents wanted to receive health information (80.2%), monetary compensation (51.4%), and smart devices (41.3%). Most participants responded that it was appropriate to carry out the project at governmental research institutes (66.9%). Respondents also had a positive attitude toward sharing their information and samples as long as it was only shared with the governmental researchers who run the project (88.0%). However, the survey participants expressed concerns about the study being time consuming or a hassle (38.1%), privacy breaches (33.6%), and the lack of returning benefits of participation (25.1%). Participants had a negative attitude toward sharing their data with researchers who are not directly involved in the RCP-PMR. Considering the future use of the database derived from this project, it will be important to communicate with the lay public as well as the RCP-PMR participants to understand their needs in participating in the forthcoming study and to improve their understanding of the goals of the project, and how data sharing can contribute to disease research and prevention. The RCP-PMR should consider building an efficient citizen-participation program and privacy protection for the research participants.

Registry stakeholders

Clinical registries are health information systems, which have the mission to collect multidimensional real-world data over the long term, and to generate relevant information and actionable knowledge to address current serious healthcare problems.

This article provides an overview of clinical registries and their relevant stakeholders, focussing on registry structure and functioning, each stakeholder’s specific interests, and on their involvement in the registry’s information input and output.

Stakeholders of clinical registries include the patients, healthcare providers (professionals and facilities), financiers (government, insurance companies), public health and regulatory agencies, industry, the research community and the media.

The article discusses (1) challenges in stakeholder interaction and how to strengthen the central role of the patient, (2) the importance of adding cost reporting to enable informed value choices, and (3) the need for proof of clinical and public health utility of registries.

In its best form, a registry is a mission-driven, independent stakeholder–registry team collaboration that enables rapid, transparent and open-access knowledge generation and dissemination.

Cite this article: EFORT Open Rev 2019;4 DOI: 10.1302/2058-5241.4.180077

Weighing benefits and risks in aspects of security, privacy and adoption of technology in a value-based healthcare system

Background

Technology can potentially enable the implementation of a value-based healthcare system, where the impact of quality of care is offered at optimised cost for maximised patient benefit. Technology can deliver value by aiding in data collection to evaluate outcomes and measure costs on a patient and population level. Healthcare organisations, however, face several challenges and risks that result almost exclusively from the use of these technologies.

Discussion

Some challenges associated with healthcare technology include their unsustainability, due to lack of scale-up plans and timely evaluations. Other risks include noncompliance with data protection policies, inadequate data governance, and overestimated expectations resulting from the rapid introduction of new technologies.

Conclusion

Organisations need to consider the risks and challenges associated with the use of technology and develop comprehensive strategies that mitigate factors leading to non-adoption and to realise benefits for achieving a value-based healthcare system.