No file available
To read the file of this research,
you can request a copy directly from the authors.
Transparency and the Secondary Use of Health Data: A Scoping Review of What Should Be Communicated to the Members of the Public, How and at What Conditions (Preprint)
Abstract
BACKGROUND
Learning Health Systems rely on the secondary use of health data to improve care. Transparency regarding this secondary use is frequently cited as necessary to increase patient awareness, support alternative approaches to consent, and foster trust.
OBJECTIVE
To review the current published literature to identify different stakeholders’ perspectives and recommendations on what exactly should be communicated to members of the public regarding the secondary use of health data for research, how and at what conditions.
METHODS
Using PRISMA-ScR guidelines, we conducted a scoping review through several bibliographic databases (Medline, CINAHL, PsycINFO, Scopus, Cochrane Database of Systematic Reviews, and PubMed) to locate a broad range of studies published in English or French up to November 2022. We included articles that reported a stakeholder’s opinion or recommendations of what should be communicated to patients or members of the public regarding the secondary use of health data for research, how to communicate the information or at what conditions. Data were collected and analyzed using an iterative thematic approach with NVivo software.
RESULTS
A total of 178 articles was included in this scoping review. Communication was deemed crucial for many purposes including: a) educating patients and members of the public on the potential benefits; b) giving some control over data use c) as a form of reciprocity and, d) as a condition to build and maintain trust. Elements that should be communicated include generic content such as governance and regulatory frameworks, scientific aims and potential future uses of the data and specific content that is relevant to each person with regards to the use of their data. 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 regards to length, avoidance of technical terms, cultural competence, and level of detail.
CONCLUSIONS
This review can serve as a foundation for evaluating current communication approaches with regards to secondary use of health data or designing future strategies. Future work will be needed to assess which strategies achieve the greatest outreach while striking a balance between transparency and utilization of resources.
ResearchGate has not been able to resolve any citations for this publication.
Background:
Precision oncology is one of the fastest-developing domains of personalized medicine and is one of many data-intensive fields. Policy for health information sharing that is informed by patient perspectives can help organizations align practice with patient preferences and expectations, but many patients are largely unaware of the complexities of how and why clinical health information is shared.
Objective:
This paper evaluates the process of public deliberation as an approach to understanding the values and preferences of current and former patients with cancer regarding the use and sharing of health information collected in the context of precision oncology.
Methods:
We conducted public deliberations with patients who had a current or former cancer diagnosis. A total of 61 participants attended 1 of 2 deliberative sessions (session 1, n=28; session 2, n=33). Study team experts led two educational plenary sessions, and trained study team members then facilitated discussions with small groups of participants. Participants completed pre- and postdeliberation surveys measuring knowledge, attitudes, and beliefs about precision oncology and data sharing. Following informational sessions, participants discussed, ranked, and deliberated two policy-related scenarios in small groups and in a plenary session. In the analysis, we evaluate our process of developing the deliberative sessions, the knowledge gained by participants during the process, and the extent to which participants reasoned with complex information to identify policy preferences.
Results:
The deliberation process was rated highly by participants. Participants felt they were listened to by their group facilitator, that their opinions were respected by their group, and that the process that led to the group’s decision was fair. Participants demonstrated improved knowledge of health data sharing policies between pre- and postdeliberation surveys, especially regarding the roles of physicians and health departments in health information sharing. Qualitative analysis of reasoning revealed that participants recognized complexity, made compromises, and engaged with trade-offs, considering both individual and societal perspectives related to health data sharing.
Conclusions:
The deliberative approach can be valuable for soliciting the input of informed patients on complex issues such as health information sharing policy. Participants in our two public deliberations demonstrated that giving patients information about a complex topic like health data sharing and the opportunity to reason with others and discuss the information can help garner important insights into policy preferences and concerns. Data on public preferences, along with the rationale for information sharing, can help inform policy-making processes. Increasing transparency and patient engagement is critical to ensuring that data-driven health care respects patient autonomy and honors patient values and expectations.
Background
Patients and publics are generally positive about data-intensive health research. However, conditions need to be fulfilled for their support. Ensuring confidentiality, security, and privacy of patients’ health data is pivotal. Patients and publics have concerns about secondary use of data by commercial parties and the risk of data misuse, reasons for which they favor personal control of their data. Yet, the potential of public benefit highlights the potential of building trust to attenuate these perceptions of harm and risk. Nevertheless, empirical evidence on how conditions for support of data-intensive health research can be operationalized to that end remains scant.
Objective
This study aims to inform efforts to design governance frameworks for data-intensive health research, by gaining insight into the preferences of patients and publics for governance policies and measures.
Methods
We distributed a digital questionnaire among a purposive sample of patients and publics. Data were analyzed using descriptive statistics and nonparametric inferential statistics to compare group differences and explore associations between policy preferences.
Results
Study participants (N=987) strongly favored sharing their health data for scientific health research. Personal decision-making about which research projects health data are shared with (346/980, 35.3%), which researchers/organizations can have access (380/978, 38.9%), and the provision of information (458/981, 46.7%) were found highly important. Health data–sharing policies strengthening direct personal control, like being able to decide under which conditions health data are shared (538/969, 55.5%), were found highly important. Policies strengthening collective governance, like reliability checks (805/967, 83.2%) and security safeguards (787/976, 80.6%), were also found highly important. Further analysis revealed that participants willing to share health data, to a lesser extent, demanded policies strengthening direct personal control than participants who were reluctant to share health data. This was the case for the option to have health data deleted at any time (P<.001) and the ability to decide the conditions under which health data can be shared (P<.001). Overall, policies and measures enforcing conditions for support at the collective level of governance, like having an independent committee to evaluate requests for access to health data (P=.02), were most strongly favored. This also applied to participants who explicitly stressed that it was important to be able to decide the conditions under which health data can be shared, for instance, whether sanctions on data misuse are in place (P=.03).
Conclusions
This study revealed that both a positive attitude toward health data sharing and demand for personal decision-making abilities were associated with policies and measures strengthening control at the collective level of governance. We recommend pursuing the development of this type of governance policy. More importantly, further study is required to understand how governance policies and measures can contribute to the trustworthiness of data-intensive health research.
The Cooperative Health Research in South Tyrol (CHRIS) is a longitudinal study in Northern Italy, using dynamic consent since its inception in 2011. The CHRIS study collects health data and biosamples for research, and foresees regular follow-ups over time. We describe the experience with the CHRIS study dynamic consent, providing an overview of its conceptualization and implementation, and of the participant-centered strategies used to assess and improve the process, directly linked to participation and communication. In order to comply with high ethical standards and to allow broadness in the areas of research, CHRIS dynamic consent was conceived as an interactive process: based on a strong governance and an ongoing tailored communication with participants, it aims to promote autonomy and to develop a trust-based engaged relationship with participants, also relevant for retention. Built within an online platform, the consent allows granular choices, which can be changed over time. In a process of co-production, participants views have been investigated and kept into account in policy development. Participants showed a high degree of participation, thus enabling the consolidation of the CHRIS resources. Even though a low change rate was reported in the baseline, participants valued the possibility of changing their informed consent choices. Communication (language-tailored, ongoing, multimedia) was important for participants, and for participation and retention. In our experience, dynamic consent was proven to be a flexible consent model, which allowed to meet ethical and legal standards for participation in research, and to accommodate participants’ and researchers’ needs.
Sommaire
Il est attendu du fonctionnement plus ouvert des administrations un regain de confiance citoyenne et de légitimité. Toutefois, les effets produits par la transparence alimentent de nombreux débats. D'abord, la relation entre transparence et confiance peut être multidirectionnelle. Ensuite, elle correspond à un équilibre fragile dans la mesure où un surplus de communication sur des enjeux sensibles peut réduire la confiance dans les organisations publiques. Enfin, la confiance se crée à partir de multiples facteurs, réduisant ainsi l'impact de la transparence. Ces différents enjeux sont analysés sur la base d'une revue de la littérature scientifique et médiatique et d'exemples.
Objectives
In Kent, Surrey and Sussex (KSS), linked health and social care datasets are in set-up phase in NHS integrated care systems (ICS), and governance models for using data for planning and research are under development. This represented an exceptional opportunity to consult with KSS citizens and work together to identify how ICSs in KSS can secure a social licence for data-linkage and data uses. Methods
We held online deliberative discussion focus groups asking KSS citizens to discuss the perceived benefits and risks of data-linkage for planning and research; to describe safeguards they expected around the data, and to describe how the public should be involved in, and communicated with, regarding governance and uses of datasets. We held one creative workshop in which participants artistically depicted their support or concerns around data. Results79 KSS citizens took part in 5 focus groups, and 7 participants attended the creative workshop. There was widespread support for data-linkage to improve efficiency of services and information flows, with the expectation that this would improve patient experience. Proposed ICS governance models were acceptable, but participants identified four key values to ensure appropriate use: acknowledging experience of stigma and discrimination; public voices being heard; holding people to account; and keeping data trails and audits. Participants gave a range of suggestions for ensuring public involvement and communication would be accessible and reach a diverse audience, such as using community champions to ensure a range of contributors, using plain language, giving concise information, building trust through mutually respectful relationships, and valuing public contributions through appropriate payment. Conclusion
Social licence theory describes expectations that organisations go beyond requirements of formal regulation and ensure transparent values of reciprocity, non-exploitation and service to the public good. Following findings from this project, ICSs in KSS are now in a good position to deliver social licence values, together with a strong public voice, to inform and determine governance arrangements for linked datasets in the region.
Assessing public and patients’ expectations and concerns about genomic data sharing is essential to promote adequate data governance and engagement in rare diseases genomics research. This cross-sectional study compared the views of 159 rare disease patients, 478 informal carers and 63 healthcare professionals in Northern Portugal about the benefits and risks of sharing genomic data for research, and its associated factors. The three participant groups expressed significantly different views. The majority of patients (84.3%) and informal carers (87.4%) selected the discovery of a cure for untreatable diseases as the most important benefit. In contrast, most healthcare professionals revealed a preference for the development of new drugs and treatments (71.4%), which was the second most selected benefit by carers (48.3%), especially by the more educated (OR (95% CI): 1.58 (1.07–2.34)). Lack of security and control over information access and the extraction of information exceeding research objectives were the two most often selected risks by patients (72.6% and 50.3%, respectively) and carers (60.0% and 60.6%, respectively). Conversely, professionals were concerned with genomic data being used to discriminate citizens (68.3%), followed by the extraction of information exceeding research objectives (54.0%). The latter risk was more frequently expressed by more educated carers (OR (95% CI): 1.60 (1.06–2.41)) and less by those with blue-collar (OR (95% CI): 0.44 (0.25–0.77) and other occupations (OR (95% CI): 0.44 (0.26–0.74)). Developing communication strategies and consent approaches tailored to participants’ expectations and needs can benefit the inclusiveness of genomics research that is key for patient-centred care.
Background:
Secondary use of clinical data for biomedical research purposes holds great potential for various types of noninterventional, data-driven studies. Patients' willingness to support research with their clinical data is a crucial prerequisite for research progress.
Objective:
The aim of the study was to learn about patients' attitudes and expectations regarding secondary use of their clinical data. In a next step, our results can inform the development of an appropriate governance framework for secondary use of clinical data for research purposes.
Methods:
A questionnaire was developed to assess the willingness of patients with cancer to provide their clinical data for biomedical research purposes, considering different conditions of data sharing and consent models. The Cancer Registry of the German federal state of Baden-Württemberg recruited a proportionally stratified random sample of patients with cancer and survivors of cancer based on a full census.
Results:
In total, 838 participants completed the survey. Approximately all participants (810/838, 96.7%) showed general willingness to make clinical data available for biomedical research purposes; however, they expected certain requirements to be met, such as comparable data protection standards for data use abroad and the possibility to renew consent at regular time intervals. Most participants (620/838, 73.9%) supported data use also by researchers in commercial companies. More than half of the participants (503/838, 60%) were willing to give up control over clinical data in favor of research benefits. Most participants expressed acceptance of the broad consent model (494/838, 58.9%), followed by data use by default (with the option to opt out at any time; 419/838, 50%); specific consent for every study showed the lowest acceptance rate (327/838, 39%). Patients expected physicians to share their data (763/838, 91.1%) and their fellow patients to support secondary use with their clinical data (679/838, 81%).
Conclusions:
Although patients' general willingness to make their clinical data available for biomedical research purposes is very high, the willingness of a substantial proportion of patients depends on additional requirements. Taking these perspectives into account is essential for designing trustworthy governance of clinical data reuse and sharing. The willingness to accept the loss of control over clinical data to enhance the benefits of research should be given special consideration.
Background
The aim of the present survey was to investigate newly discharged hospital patients’ opinions on secondary use of their hospital data and biospecimens within the context of health research in general and, more specifically, on genetic research, data sharing across borders and cooperation with the health industry.
Methods
A paper questionnaire was sent to 1049 consecutive newly discharged hospital patients.
Results
The vast majority of the respondents preferred to be informed (passive consent) or to receive no notification at all for secondary research on their health data and biospecimens (88% and 91% for data and biospecimens respectively). The rest wanted to be asked for active consent. The same trend applied for the other aspects also. 81% of respondents were positive towards genetic research without active consent. 95% were positive towards cooperating with the health industry, and 90% were positive towards data sharing.
Conclusions
These results suggest that hospital patients generally are very positive to secondary research and support the concept of opting out rather than opting in.
Background
The ability of healthcare to protect sensitive personal data in medical records and registers might influence public trust, which in turn might influence willingness to allow healthcare to use such data. The aim of this study was to examine how the general public’s trust relates to their attitudes towards uses of health data.
Methods
A stratified sample from the general Swedish population received a questionnaire about their willingness to share health data. Respondents were also asked about their trust in the management and protection of electronic health data.
Results
A large majority (81.9%) of respondents revealed high levels of trust in the ability of healthcare to protect electronic patient data. Good health was associated with significantly higher levels of trust compared to bad health. Respondents with low levels of trust were significantly less willing to allow personal data to be used for different purposes and were more inclined to insist on being asked for permission beforehand. Those with low levels of trust also perceived risks of unauthorized access to personal data to be higher and the likely damage of such unauthorized access worse, compared to those with high levels of trust.
Conclusions
Trust in the ability of healthcare to protect electronic health is generally high in Sweden. Those with higher levels of trust are more willing to let their data be used, including without informed consent. It thus seems crucial to promote trust in order to be able to reap the benefits that digitalization makes possible through increased access and use of data in healthcare.
Purpose
The aim of this study was to determine how attitudes toward the return of genomic research results vary internationally.
Methods
We analyzed the “Your DNA, Your Say” online survey of public perspectives on genomic data sharing including responses from 36,268 individuals across 22 low-, middle-, and high-income countries, and these were gathered in 15 languages. We analyzed how participants responded when asked whether return of results (RoR) would motivate their decision to donate DNA or health data. We examined variation across the study countries and compared the responses of participants from other countries with those from the United States, which has been the subject of the majority of research on return of genomic results to date.
Results
There was substantial variation in the extent to which respondents reported being influenced by RoR. However, only respondents from Russia were more influenced than those from the United States, and respondents from 20 countries had lower odds of being partially or wholly influenced than those from the United States.
Conclusion
There is substantial international variation in the extent to which the RoR may motivate people’s intent to donate DNA or health data. The United States may not be a clear indicator of global attitudes. Participants’ preferences for return of genomic results globally should be considered.
The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial intelligence (AI) in genomics are critical public issues in medical care and scientific research. The present study was aimed to examine the awareness, knowledge, and attitude of the Saudi society towards the SHGP, the sharing and privacy of genetic data resulting from the SHGP, and the role of AI in genetic data analysis and regulations. Results of a questionnaire survey with 804 respondents revealed moderate awareness and attitude towards the SHGP and minimal knowledge regarding its benefits and applications. Respondents demonstrated a low level of knowledge regarding the privacy of genetic data. A generally positive attitude was found towards the outcomes of the SHGP and genetic data sharing for medical and scientific research. The highest level of knowledge was detected regarding AI use in genetic data analysis and privacy regulation. We recommend that the SHGP's regulators launch awareness campaigns and educational programs to increase and improve public awareness and knowledge regarding the SHGP's benefits and applications. Furthermore, we propose a strategy for genetic data sharing which will facilitate genetic data sharing between institutions and advance Personalized Medicine in genetic diseases' diagnosis and treatment.
Background
During the COVID-19 pandemic, but also in the context of previous epidemic diseases, mobile apps for smartphones were developed with different goals and functions, such as digital contact tracing, test management, symptom monitoring, quarantine compliance, and epidemiological and public health research.
Objective
The aim of this study was to explore the potential for the acceptance of research-orientated apps (ROAs) in the German population. To this end, we identified distinctive attitudes toward pandemic apps and data sharing for research purposes among smartphone users in general and with a focus on differences in attitudes between app users and nonusers in particular.
Methods
We conducted a cross-sectional, national, telephone-based survey of 1003 adults in Germany, of which 924 were useable for statistical analysis. The 17-item survey assessed current usage of pandemic apps, motivations for using or not using pandemic apps, trust in app distributors and attitudes toward data handling (data storage and transmission), willingness to share coded data with researchers using a pandemic app, social attitudes toward app use, and demographic and personal characteristics.
ResultsA vast majority stated that they used a smartphone (778/924, 84.2%), but less than half of the smartphone users stated that they used a pandemic app (326/778, 41.9%). The study focused on the subsample of smartphone users. Interestingly, when asked about preferred organizations for data storage and app distribution, trust in governmental (federal or state government, regional health office), public-appointed (statutory health insurance), or government-funded organizations (research institutes) was much higher than in private organizations (private research institutions, clinics, health insurances, information technology [IT] companies). Having a university degree significantly (P
Background
The SARS-CoV-2 pandemic has highlighted once more the great need for comprehensive access to, and uncomplicated use of, pre-existing patient data for medical research. Enabling secondary research-use of patient-data is a prerequisite for the efficient and sustainable promotion of translation and personalisation in medicine, and for the advancement of public-health. However, balancing the legitimate interests of scientists in broad and unrestricted data-access and the demand for individual autonomy, privacy and social justice is a great challenge for patient-based medical research.
Methods
We therefore conducted two questionnaire-based surveys among North-German outpatients (n = 650) to determine their attitude towards data-donation for medical research, implemented as an opt-out-process.
Results
We observed a high level of acceptance (75.0%), the most powerful predictor of a positive attitude towards data-donation was the conviction that every citizen has a duty to contribute to the improvement of medical research (> 80% of participants approving data-donation). Interestingly, patients distinguished sharply between research inside and outside the EU, despite a general awareness that universities and public research institutions cooperate with commercial companies, willingness to allow use of donated data by the latter was very low (7.1% to 29.1%, depending upon location of company). The most popular measures among interviewees to counteract reservations against commercial data-use were regulation by law (61.4%), stipulating in the process that data are not sold or resold (84.6%). A majority requested control of both the use (46.8%) and the protection (41.5%) of the data by independent bodies.
Conclusions
In conclusion, data-donation for medical research, implemented as a combination of legal entitlement and easy-to-exercise-right to opt-out, was found to be widely supported by German patients and therefore warrants further consideration for a transposition into national law.
Objective
Researchers are increasingly collecting large amounts of deidentified data about individuals to address important health-related challenges and answer fundamental questions. Current US federal regulations permit researchers to use already collected and stored deidentified health-related data from a variety of sources without seeking consent from patients. The objective of this study was to investigate public views on the policies and processes institutions have in place for accessing, using, and sharing of data.
Materials and Methods
We conducted 5 focus groups with individuals living within a 20-mile radius of the local academic medical center. We also held a focus group with undergraduates at a local university.
Results
A total of 37 individuals participated, ages 18–76. Most participants were not surprised that researchers accessed and used deidentified personal information for research, and were supportive of this practice. Transparency was important. Participants wanted to know when their data were accessed, for what purpose, and by whom. Some wanted to have some control over the use of their data valuing the chance to opt-out. Finally, participants supported establishment of an advisory council or group with responsibility for deciding what data were used, who was accessing those data, and whether data could be shared.
Discussion and Conclusions
The trust people have in their local institutions should be considered fragile, and institutions should not take that trust for granted. How institutions choose to govern patients’ data and what voices are included in decisions about use and access are critical to maintaining the trust of the public.
Background
The development of Precision Medicine strategies requires high-dimensional phenotypic and genomic data, both of which are highly privacy-sensitive data types. Conventional data management systems lack the capabilities to sufficiently handle the expected large quantities of such sensitive data in a secure manner. PROMISE is a genetic data management concept that implements a highly secure platform for data exchange while preserving patient interests, privacy, and autonomy.
Methods
The concept of PROMISE to democratize genetic data was developed by an interdisciplinary team. It integrates a sophisticated cryptographic concept that allows only the patient to grant selective access to defined parts of his genetic information with single DNA base-pair resolution cryptography. The PROMISE system was developed for research purposes to evaluate the concept in a pilot study with nineteen cardiomyopathy patients undergoing genotyping, questionnaires, and longitudinal follow-up.
Results
The safety of genetic data was very important to 79%, and patients generally regarded the data as highly sensitive. More than half the patients reported that their attitude towards the handling of genetic data has changed after using the PROMISE app for 4 months (median). The patients reported higher confidence in data security and willingness to share their data with commercial third parties, including pharmaceutical companies (increase from 5 to 32%).
Conclusion
PROMISE democratizes genomic data by a transparent, secure, and patient-centric approach. This clinical pilot study evaluating a genetic data infrastructure is unique and shows that patient’s acceptance of data sharing can be increased by patient-centric decision-making.
Graphic abstract
In the UK, genomic health data is being generated in three major contexts: the healthcare system (based on clinical indication), in large scale research programmes, and for purchasers of direct-to-consumer genetic tests. The recently delivered hybrid clinical/research programme, 100,000 Genomes Project set the scene for a new Genomic Medicine Service, through which the National Health Service aims to deliver consistent and equitable care informed by genomics, while providing data to inform academic and industry research and development. In parallel, a large scale research study, Our Future Health, has UK Government and Industry investment and aims to recruit 5 million volunteers to support research intended to improve early detection, risk stratification, and early intervention for chronic diseases. To explore how current models of genomic health data generation intersect, and to understand clinical, ethical, legal, policy and social issues arising from this intersection, we conducted a series of five multidisciplinary panel discussions attended by 28 invited stakeholders. Meetings were recorded and transcribed. We present a summary of issues identified: genomic test attributes; reasons for generating genomic health data; individuals’ motivation to seek genomic data; health service impacts; role of genetic counseling; equity; data uses and security; consent; governance and regulation. We conclude with some suggestions for policy consideration.
Background
The point of care in many health systems is increasingly a point of health data generation, data which may be shared and used in a variety of ways by a range of different actors.
Aim
We set out to gather data about the perspectives on health data-sharing of people living in North East England who have been underrepresented within other public engagement activities and who are marginalized in society.
Methods
Multi-site ethnographic fieldwork was carried out in the Teesside region of England over a 6-month period in 2019 as part of a large-scale health data innovation program called Connected Health Cities. Organizations working with marginalized groups were contacted to recruit staff, volunteers, and beneficiaries for participation in qualitative research. The data gathered were analyzed thematically and vignettes constructed to illustrate findings.
Results
Previous encounters with health and social care professionals and the broader socio-political contexts of people’s lives shape the perspectives of people from marginalized groups about sharing of data from their health records. While many would welcome improved care, the risks to people with socially produced vulnerabilities must be appreciated by those advocating systems that share data for personalized medicine or other forms of data-driven care.
Conclusion
Forms of innovation in medicine which rely on greater data-sharing may present risks to groups and individuals with existing vulnerabilities, and advocates of these innovations should address the lack of trustworthiness of those receiving data before asking that people trust new systems to provide health benefits.
Background
The use of government health data for secondary purposes, such as monitoring the quality of hospital services, researching the health needs of populations, and testing how well new treatments work, is increasing. This increase in the secondary uses of health data has led to increased interest in what the public thinks about data sharing, in particular, the possibilities of sharing with the private sector for research and development. Although international evidence demonstrates broad public support for the secondary use of health data, this support does not extend to sharing health data with the private sector. If governments intend to share health data with the private sector, knowing what the public thinks will be important. This paper reports a national survey to explore public attitudes in Australia toward sharing health data with private companies for research on and development of therapeutic drugs and medical devices.
Objective
This study aims to explore public attitudes in Australia toward sharing government health data with the private sector.
Methods
A web-based survey tool was developed to assess attitudes about sharing government health data with the private sector. A market research company was employed to administer the web-based survey in June 2019.
Results
The survey was completed by 2537 individuals residing in Australia. Between 51.8% and 57.98% of all participants were willing to share their data, with slightly fewer in favor of sharing to improve health services (51.99%) and a slightly higher proportion in favor of sharing for research and development (57.98%). There was a preference for opt-in consent (53.44%) and broad support for placing conditions on sharing health information with private companies (62% to 91.99%). Wide variability was also observed in participants’ views about the extent to which the private sector could be trusted and how well they would behave if entrusted with people’s health information. In their qualitative responses, the participants noted concerns about private sector corporate interests, corruption, and profit making and expressed doubt about the Australian government’s capacity to manage data sharing safely. The percentages presented are adjusted against the Australian population.
Conclusions
This nationally representative survey provides preliminary evidence that Australians are uncertain about sharing their health data with the private sector. Although just over half of all the respondents supported sharing health data with the private sector, there was also strong support for strict conditions on sharing data and for opt-in consent and significant concerns about how well the private sector would manage government health data. Addressing public concern about sharing government health data with the private sector will require more and better engagement to build community understanding about how agencies can collect, share, protect, and use their personal data.
Background
The meaningful sharing of health data between different stakeholders is central to the advancement of science and to improve care offered to individual patients. However, it is important that the interests of individual stakeholders involved in this data sharing ecosystem are taken into account to ensure fair data sharing practices. In this regard, this qualitative study investigates such practices from the perspectives of a subset of relevant Swiss expert stakeholders, using a distributive justice lens.
Methods
Using purposive and snowball sampling methodologies, 48 expert stakeholders from the Swiss healthcare and research domains were recruited for semi-structured interviews. After the experts had consented, the interviews were audio-recorded and transcribed verbatim, but omitting identifying information to ensure confidentiality and anonymity. A thematic analysis using a deductive approach was conducted to identify fair data sharing practices for secondary research purposes. Themes and subthemes were then identified and developed during the analysis.
Results
Three distributive justice themes were identified in the data sharing negotiation processes, and these are: (i) effort , which was subcategorized into two subthemes (i.e. a claim to data reciprocity and other reciprocal advantages, and a claim to transparency on data re-use), (ii) compensation , which was subcategorized into two subthemes (i.e. a claim to an academic compensation and a claim to a financial compensation), and lastly, (iii) contribution , i.e. the significance of data contributions should be matched with a corresponding reward.
Conclusions
This qualitative study provides insights, which could inform policy-making on claims and incentives that encourage Swiss expert stakeholders to share their datasets. Importantly, several claims have been identified and justified under the basis of distributive justice principles, whilst some are more debatable and likely insufficient in justifying data sharing activities. Nonetheless, these claims should be taken seriously and discussed more broadly. Indeed, promoting health research while ensuring that healthcare systems guarantee better services, it is paramount to ensure that solutions developed are sustainable, provide fair criteria for academic careers and promote the sharing of high quality data to advance science.
Background:
Sharing patient data can help drive scientific advances and improve patient care, but service users are concerned about how their data are used. When the National Health Service proposes to scrape general practitioner records, it is very important that we understand these concerns in some depth.
Objective:
This study aims to investigate views of mental health service users on acceptable data sharing to provide clear recommendations for future data sharing systems.
Methods:
A total of 4 focus groups with 4 member-checking groups were conducted via the internet between October 2020 and March 2021, with a total of 22 service users in the United Kingdom. Thematic analysis was used to identify the themes.
Results:
Six main themes, with several subthemes were identified, such as the purpose of data sharing-for profit, public good, and continuation of care; discrimination through the misattribution of physical symptoms to mental health conditions (ie, diagnostic overshadowing) alongside the discrimination of individuals or groups within society (ie, institutional discrimination); safeguarding data by preserving anonymity and confidentiality, strengthening security measures, and holding organizations accountable; data accuracy and informed consent-increasing transparency about data use and choice; and incorporating service user involvement in system governance to provide insight and increase security.
Conclusions:
This study extends the limited research on the views and concerns of mental health service users regarding acceptable data sharing. If adopted, the recommendations should improve the confidence of service users in sharing their data. The five recommendations include screening to ensure that data sharing benefits the public, providing service users with information about how their data are shared and what for, highlighting the existing safeguarding procedures, incorporating service user involvement, and developing tailored training for health care professionals to address issues of diagnostic overshadowing and inaccurate health records. Adopting such systems would aid in data sharing for legitimate interests that will benefit patients and the National Health Service.
Background
For evidence-based decision-making, there is a need for quality, timely, relevant and accessible information at each level of the health system. Limited use of local data at each level of the health system is reported to be a main challenge for evidence-based decision-making in low- and middle-income countries. Although evidence is available on the timeliness and quality of local data, we know little about how it is used for decision-making at different levels of the health system. Therefore, this study aimed to assess the level of data use and its effect on data quality and shared accountability at different levels of the health system.
Methods
An implementation science study was conducted using key informants and document reviews between January and September 2017. A total of 21 key informants were selected from community representatives, data producers, data users and decision-makers from the community to the regional level. Reviewed documents include facility reports, district reports, zonal reports and feedback in supervision from the district. Thematic content analysis was performed for the qualitative data.
Results
Respondents reported that routine data use for routine decision-making was low. All health facilities and health offices have a performance monitoring team, but these were not always functional. Awareness gaps, lack of motivating incentives, irregularity of supportive supervision, lack of community engagement in health report verification as well as poor technical capacity of health professionals were found to be the major barriers to data use. The study also revealed that there are no institutional or national-level regulations or policies on the accountability mechanisms related to health data. The community-level Health Development Army programme was found to be a strong community engagement approach that can be leveraged for data verification at the source of community data.
Conclusion
The culture of using routine data for decision-making at the local level was found to be low. Strengthening the capacity of health workers and performance monitoring teams, introducing incentive mechanisms for data use, engaging the community in data verification and introducing accountability mechanisms for health data are essential to improve data use and quality.
Background
The rise of Big Data-driven health research challenges the assumed contribution of medical research to the public good, raising questions about whether the status of such research as a common good should be taken for granted, and how public trust can be preserved. Scandals arising out of sharing data during medical research have pointed out that going beyond the requirements of law may be necessary for sustaining trust in data-intensive health research. We propose building upon the use of a social licence for achieving such ethical governance.
Main text
We performed a narrative review of the social licence as presented in the biomedical literature. We used a systematic search and selection process, followed by a critical conceptual analysis. The systematic search resulted in nine publications. Our conceptual analysis aims to clarify how societal permission can be granted to health research projects which rely upon the reuse and/or linkage of health data. These activities may be morally demanding. For these types of activities, a moral legitimation, beyond the limits of law, may need to be sought in order to preserve trust. Our analysis indicates that a social licence encourages us to recognise a broad range of stakeholder interests and perspectives in data-intensive health research. This is especially true for patients contributing data. Incorporating such a practice paves the way towards an ethical governance, based upon trust. Public engagement that involves patients from the start is called for to strengthen this social licence.
Conclusions
There are several merits to using the concept of social licence as a guideline for ethical governance. Firstly, it fits the novel scale of data-related risks; secondly, it focuses attention on trustworthiness; and finally, it offers co-creation as a way forward. Greater trust can be achieved in the governance of data-intensive health research by highlighting strategic dialogue with both patients contributing the data, and the public in general. This should ultimately contribute to a more ethical practice of governance.
Background
This study aims to identify a novel potential use for web portals in health care and health research: their adoption for the purposes of rapidly sharing health research findings with clinicians, scientists, and patients. In the era of precision medicine and learning health systems, the translation of research findings into targeted therapies depends on the availability of big data and emerging research results. Web portals may work to promote the availability of novel research, working in tandem with traditional scientific publications and conference proceedings.
Objective
This study aims to assess the potential use of web portals, which facilitate the sharing of health research findings among researchers, clinicians, patients, and the public. It also summarizes the potential legal, ethical, and policy implications associated with such tools for public use and in the management of patient care for complex diseases.
Methods
This study broadly adopts the methods for scoping literature reviews outlined by Arskey and O’Malley in 2005. Raised by the integration of web portals into patient care for complex diseases, we systematically searched 3 databases, PubMed, Scopus, and WestLaw Next, for sources describing web portals for sharing health research findings among clinicians, researchers, and patients and their associated legal, ethical, and policy challenges. Of the 719 candidate source citations, 22 were retained for the review.
Results
We found varied and inconsistent treatment of web portals for sharing health research findings among clinicians, researchers, and patients. Although the literature supports the view that portals of this kind are potentially highly promising, they remain novel and are not yet widely adopted. We also found a wide range of discussions on the legal, ethical, and policy issues related to the use of web portals to share research data.
Conclusions
We identified 5 important legal and ethical challenges: privacy and confidentiality, patient health literacy, equity, training, and decision-making. We contend that each of these has meaningful implications for the increased integration of web portals into clinical care.
Background : The collection and sharing of genomic and health data underpins global efforts to develop genomic medicine services. ‘Your DNA, Your Say’ is a cross-sectional survey with the goal of gathering lay public attitudes toward the access and sharing of deoxyribonucleic acid (DNA) information and medical information. It suggests significant international variation in the willingness to share information, and in trust in the actors associated with the collection and use of this information. This paper explores these questions in the Italian context.
Methods : The Italian Your DNA, Your Say campaign led to the collection of 1229 valid questionnaires. The sample was analysed using standard descriptive statistics. We described the sample in terms of gender, age ranges and self-reported religiosity, and split the sample amongst the five typically studied Italian macro-areas to explore regional variation. We analysed the relationship between these factors and trust and willingness to share medical and DNA information.
Results : The majority of the sample, across all socio-demographics, were willing to share DNA and health information with all entities considered except for-profit researchers. Respondents tended not to trust institutions beyond their own doctor. There was no difference between Italian regions.
Conclusions : Despite the generally positive attitude towards sharing, we suggest that the lack of trust in non-profit researchers and the government needs to be better understood to inform public communication projects around genomics in the future and to enhance awareness of DNA and medical information in Italy.
Background:
Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to healthcare. However, for it to be successful, large amounts of health data are required for the training and testing of algorithms. As such, there is a need to understand the perspectives and viewpoints of patients regarding the use of their health data in AI research.
Objective:
To survey a large sample of patients to identify current awareness of health data research, opinions and views on data sharing for the purposes of AI research, and viewpoints on the use of AI technology on healthcare data.
Methods:
A cross-sectional survey with patients was conducted at a large multi-site teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data.
Results:
A total of 408 participants completed the survey. Respondents had low levels of prior knowledge of AI in general. Most were comfortable with sharing health data with the NHS (77.9%) or universities (65.7%), but far fewer with commercial organisations such as technology companies (26.4%). The majority endorsed AI research on healthcare data (87.4%) and healthcare imaging (86.4%) in a university setting, providing that concerns about privacy, re-identification of anonymised health care data and consent processes were addressed.
Conclusions:
There is significant variation in patient perception, levels of support, and understanding of health data research and AI. There is a need for greater public engagement and debate to ensure the acceptability of AI research and its successful integration into clinical practice in the future.
Clinicaltrial:
Background
The advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, particularly research activities. Current consent models in Quebec were not established with the context of LHSs in mind and do not support the agility and transparency required to obtain consent from all involved, especially the citizens. Therefore, a new approach to consent is needed. Previous work identified the meta-consent model as a promising alternative to fulfill the requirements of LHSs, particularly large-scale deployments. We elicited the public’s attitude toward the meta-consent model to evaluate if the model could be understood by the citizens and would be deemed acceptable to prepare for its possible implementation in Quebec.
Methods
Eight focus groups, with a total of 63 members of the general public from various backgrounds were conducted in Quebec, Canada, in 2019. Explicit attention was given to literacy levels, language spoken at home and rural vs urban settings. We assessed attitudes, concerns and facilitators regarding key components of the meta-consent model: predefined categories to personalized consent requests, a dynamic web-based infrastructure to record meta-consent, and default settings. To analyse the discussions, a thematic content analysis was performed using a qualitative software.
Results
Our findings showed that participants were supportive of this new approach of consent as it promotes transparency and offers autonomy for the management of their health data. Key facilitators were identified to be considered in the implementation of a meta-consent model in the Quebec LHSs: information and transparency, awareness campaigns, development of educational tools, collaboration of front-line healthcare professionals, default settings deemed acceptable by the society as well as close partnerships with recognized and trusted institutions.
Conclusions
This qualitative study reveals the openness of a sample of the Quebec population regarding the meta-consent model for secondary use of health data for research. This first exploratory study conducted with the public is an important step in guiding decision-makers in the next phases of implementing the various strategies to support access and use of health data in Quebec.
Background:
England operates a National Data Opt-Out (NDOO) for the secondary use of confidential health data for research and planning. We hypothesised that public awareness and support for the secondary use of health data and the NDOO would vary by participant demography and healthcare experience. We explored patient/public awareness and perceptions of secondary data use, grouping potential researchers into National Health Service (NHS), academia or commercial. We assessed awareness of the NDOO system amongst patients, carers, healthcare staff and the public. We co-developed recommendations to consider when sharing unconsented health data for research.
Methods:
A patient and public engagement program, co-created and including patient and public workshops, questionnaires and discussion groups regarding anonymised health data use.
Results:
There were 350 participants in total. Central concerns for health data use included unauthorised data re-use, the potential for discrimination and data sharing without patient benefit. 94% of respondents were happy for their data to be used for NHS research, 85% for academic research and 68% by health companies, but less than 50% for non-healthcare companies and opinions varied with demography and participant group. Questionnaires showed that knowledge of the NDOO was low, with 32% of all respondents, 53% of all NHS staff and 29% of all patients aware of the NDOO. Recommendations to guide unconsented secondary health data use included that health data use should benefit patients; data sharing decisions should involve patients/public. That data should remain in close proximity to health services with the principles of data minimisation applied. Further, that there should be transparency in secondary health data use, including publicly available lists of projects, summaries and benefits. Finally, organisations involved in data access decisions should participate in programmes to increase knowledge of the NDOO, to ensure public members were making informed choices about their own data.
Conclusion:
The majority of participants in this study reported that the use of healthcare data for secondary purposes was acceptable when accessed by NHS. Academic and health-focused companies. However, awareness was limited, including of the NDOO. Further development of publicly-agreed recommendations for secondary health data use may improve both awareness and confidence in secondary health data use.
Background:
Third-party cloud-based data analysis applications are proliferating in electronic health (eHealth) because of the expertise offered and their monetary advantage. However, privacy and security are critical concerns when handling sensitive medical data in the cloud. Technical advances based on "crypto magic" in privacy-preserving machine learning (ML) enable data analysis in encrypted form for maintaining confidentiality. Such privacy-enhancing technologies (PETs) could be counterintuitive to relevant stakeholders in eHealth, which could in turn hinder adoption; thus, more attention is needed on human factors for establishing trust and transparency.
Objective:
The aim of this study was to analyze eHealth expert stakeholders' perspectives and the perceived tradeoffs in regard to data analysis on encrypted medical data in the cloud, and to derive user requirements for development of a privacy-preserving data analysis tool.
Methods:
We used semistructured interviews and report on 14 interviews with individuals having medical, technical, or research expertise in eHealth. We used thematic analysis for analyzing interview data. In addition, we conducted a workshop for eliciting requirements.
Results:
Our results show differences in the understanding of and in trusting the technology; caution is advised by technical experts, whereas patient safety assurances are required by medical experts. Themes were identified with general perspectives on data privacy and practices (eg, acceptance of using external services), as well as themes highlighting specific perspectives (eg, data protection drawbacks and concerns of the data analysis on encrypted data). The latter themes result in requiring assurances and conformance testing for trusting tools such as the proposed ML-based tool. Communicating privacy, and utility benefits and tradeoffs with stakeholders is essential for trust. Furthermore, stakeholders and their organizations share accountability of patient data. Finally, stakeholders stressed the importance of informing patients about the privacy of their data.
Conclusions:
Understanding the benefits and risks of using eHealth PETs is crucial, and collaboration among diverse stakeholders is essential. Assurances of the tool's privacy, accuracy, and patient safety should be in place for establishing trust of ML-based PETs, especially if used in the cloud.
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.
The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for clinicians, researchers, policy- and decision-makers, funders, publishers, public health experts, disaster preparedness and response experts, infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations), and other potential users. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.
Background
Public trust is central to the collection of genomic and health data and the sustainability of genomic research. To merit trust, those involved in collecting and sharing data need to demonstrate they are trustworthy. However, it is unclear what measures are most likely to demonstrate this.
Methods
We analyse the ‘Your DNA, Your Say’ online survey of public perspectives on genomic data sharing including responses from 36,268 individuals across 22 low-, middle- and high-income countries, gathered in 15 languages. We examine how participants perceived the relative value of measures to demonstrate the trustworthiness of those using donated DNA and/or medical information. We examine between-country variation and present a consolidated ranking of measures.
Results
Providing transparent information about who will benefit from data access was the most important measure to increase trust, endorsed by more than 50% of participants across 20 of 22 countries. It was followed by the option to withdraw data and transparency about who is using data and why. Variation was found for the importance of measures, notably information about sanctions for misuse of data—endorsed by 5% in India but almost 60% in Japan. A clustering analysis suggests alignment between some countries in the assessment of specific measures, such as the UK and Canada, Spain and Mexico and Portugal and Brazil. China and Russia are less closely aligned with other countries in terms of the value of the measures presented.
Conclusions
Our findings highlight the importance of transparency about data use and about the goals and potential benefits associated with data sharing, including to whom such benefits accrue. They show that members of the public value knowing what benefits accrue from the use of data. The study highlights the importance of locally sensitive measures to increase trust as genomic data sharing continues globally.
Objective: To improve the safety and quality of patient care in hospitals by shaping clinical pathways throughout the patient journey.
Study Setting: A risk model designed for healthcare organizations in the context of the challenges arising from comorbidity and other treatment-related complexities.
Study Design: The core of the model is the patient and his intra-hospital journey, which is analyzed using a data-driven approach. The structure of a predictive model to support organizational and clinical decision-making activities is explained. Data relating to each step of the intra-hospital journey (from hospital admission to discharge) are extracted from clinical records.
Principal Findings: The proposed approach is feasible and can be used effectively to improve safety and quality. It enables the evaluation of clinical risks at each step of the patient journey.
Conclusion: Based on data from real cases, the model can record and calculate, over time, variables and behaviors that affect the safety and quality of healthcare organizations. This provides a greater understanding of healthcare processes and their complexity which can, in turn, advance research relating to clinical pathways and improve strategies adopted by organizations.
Background
In this article, we address questions regarding how people consider what they do or do not consent to and the reasons why. This article presents the findings of a citizen forum study conducted by the University of Geneva in partnership with the Geneva University Hospitals to explore the opinions and concerns of members of the public regarding predictive oncology, genetic sequencing, and cancer.
Methods
This paper presents the results of a citizen forum that included 73 participants. A research tool titled "the mechanics of consent" was designed for this study. This tool is a table encouraging participants to reflect on social and research actors, types of data, and desired levels of control while sharing different types of data with different actors. Participants’ discussion that led to the completion of each table were audio-recorded, transcribed, and analyzed using thematic analysis.
Results
The results are a compilation of responses from the mechanics of consent tool divided into two sections; the first presents quantitative results of collective responses regarding attitudes to consent to donate their data. The second section present qualitative findings emerged from the discussion amongst participants.
Discussion
Choice and control of personal data is crucial for the public to be able to decide who and how to trust. Key information to be disclosed to potential research participants shall include information about potential risks and benefits; who will be accessing and using their data; as well as assurances that their choice will be respected. Furthermore, researchers ought to make sure they are trustworthy, by acting in a competent, reliable, and honest manner. Governance systems ought to be better equipped to address ethical issues raise by the growing presence of non-traditional research actors, consent of exchanges of data via digital devices and online activity such as social media and fairness of data trading. Finally, informed consent is one of the various elements that contribute to conducting ethical research. More needs to be done to strengthen governance and ensure adequate protection of research participants, particularly to address issues related to predictive health analytics.
Background
Novel consumer and lifestyle data, such as those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers seeking to understand diet- and exercise-related risk factors for diseases. However, limited research has addressed public attitudes toward linking these data with individual health records for research purposes. Data linkage, combining data from multiple sources, provides the opportunity to enhance preexisting data sets to gain new insights.
Objective
The aim of this study is to identify key barriers to data linkage and recommend safeguards and procedures that would encourage individuals to share such data for potential future research.
Methods
The LifeInfo Survey consulted the public on their attitudes toward sharing consumer and lifestyle data for research purposes. Where barriers to data sharing existed, participants provided unstructured survey responses detailing what would make them more likely to share data for linkage with their health records in the future. The topic modeling technique latent Dirichlet allocation was used to analyze these textual responses to uncover common thematic topics within the texts.
Results
Participants provided responses related to sharing their store loyalty card data (n=2338) and health and fitness app data (n=1531). Key barriers to data sharing identified through topic modeling included data safety and security, personal privacy, requirements of further information, fear of data being accessed by others, problems with data accuracy, not understanding the reason for data linkage, and not using services that produce these data. We provide recommendations for addressing these issues to establish the best practice for future researchers interested in using these data.
Conclusions
This study formulates a large-scale consultation of public attitudes toward this kind of data linkage, which is an important first step in understanding and addressing barriers to participation in research using novel consumer and lifestyle data.
This paper reports survey findings on the Swiss public’s willingness, attitudes, and concerns regarding personalized health research participation by providing health information and biological material. The survey reached a sample of 15,106 Swiss residents, from which we received 5,156 responses (34.1% response rate). The majority of respondents were aware of research using human biological samples (71.0%) and held a positive opinion towards this type of research (62.4%). Of all respondents, 53.6% indicated that they would be willing to participate in a personalized health research project. Willingness to participate was higher in younger, higher educated, non-religious respondents with a background in the health sector. Respondents were more willing to provide ‘traditional’ types of health data, such as health questionnaires, blood or biological samples, as opposed to social media or app-related data. All respondents valued the return of individual research results, including risk for diseases for which no treatment is available. Our findings highlight that alongside general positive attitudes towards personalized health research using data and samples, respondents have concerns about data privacy and re-use. Concerns included potential discrimination, confidentiality breaches, and misuse of data for commercial or marketing purposes. The findings of this large-scale survey can inform Swiss research institutions and assist policymakers with adjusting practices and developing policies to better meet the needs and preferences of the public. Efforts in this direction could focus on research initiatives engaging in transparent communication, education, and engagement activities, to increase public understanding and insight into data sharing activities, and ultimately strengthen personalized health research efforts.
Background
Immense volumes of personal health information (PHI) are required to realize the anticipated benefits of artificial intelligence in clinical medicine. To maintain public trust in medical research, consent policies must evolve to reflect contemporary patient preferences.
Methods
Patients were invited to complete a 27-item survey focusing on: (a) broad versus specific consent; (b) opt-in versus opt-out approaches; (c) comfort level sharing with different recipients; (d) attitudes towards commercialization; and (e) options to track PHI use and study results.
Results
222 participants were included in the analysis; 83% were comfortable sharing PHI with researchers at their own hospital, although younger patients (≤ 49 years) were more uncomfortable than older patients (50 + years; 13% versus 2% uncomfortable, p < 0.05). While 56% of patients preferred broad consent, 38% preferred specific consent; 6% preferred not sharing at all. The majority of patients (63%) preferred to be asked for permission before entry into a contact pool. Again, this trend was more pronounced for younger patients (≤ 49 years: 76%). Approximately half of patients were uncomfortable sharing PHI with commercial enterprises (51% uncomfortable, 27% comfortable, 22% neutral). Most patients preferred to track PHI usage (61%), with the highest proportion once again reported by the youngest patients (≤ 49 years: 71%). A majority of patients also wished to be notified regarding study results (70%).
Conclusions
While most patients were willing to share their PHI with researchers within their own institution, many preferred a transparent and reciprocal consent process. These data also suggest a generational shift, wherein younger patients preferred more specific consent options. Modernizing consent policies to reflect increased autonomy is crucial in fostering sustained public engagement with medical research.
A survey was conducted to assess citizens, research ethics committee members, and researchers’ attitude toward information and consent for the secondary use of health data for research within learning health systems (LHSs). Results show that the reuse of health data for research to advance knowledge and improve care is valued by all parties; consent regarding health data reuse for research has fundamental importance particularly to citizens; and all respondents deemed important the existence of a secure website to support the information and consent processes. This survey was part of a larger project that aims at exploring public perspectives on alternate approaches to the current consent models for health data reuse to take into consideration the unique features of LHSs. The revised model will need to ensure that citizens are given the opportunity to be better informed about upcoming research and have their say, when possible, in the use of their data.
Background
The transition to electronic health records offers the potential for big data to drive the next frontier in healthcare improvement. Yet there are multiple barriers to harnessing the power of data. The Learning Health System (LHS) has emerged as a model to overcome these barriers, yet there remains limited evidence of impact on delivery or outcomes of healthcare.
Objective
To gather evidence on the effects of LHS data hubs or aligned models that use data to deliver healthcare improvement and impact. Any reported impact on the process, delivery or outcomes of healthcare was captured.
Methods
Systematic review from CINAHL, EMBASE, MEDLINE, Medline in-process and Web of Science PubMed databases, using learning health system, data hub, data-driven, ehealth, informatics, collaborations, partnerships, and translation terms. English-language, peer-reviewed literature published between January 2014 and Sept 2019 was captured, supplemented by a grey literature search. Eligibility criteria included studies of LHS data hubs that reported research translation leading to health impact.
Results
Overall, 1076 titles were identified, with 43 eligible studies, across 23 LHS environments. Most LHS environments were in the United States (n = 18) with others in Canada, UK, Sweden and Australia/NZ. Five (21.7%) produced medium-high level of evidence, which were peer-reviewed publications.
Conclusions
LHS environments are producing impact across multiple continents and settings.
Background:
When designing and developing patient decision aids, guidelines recommend involving patients and stakeholders. There are myriad ways to do this. We aimed to describe how such involvement occurs by synthesizing reports of patient decision aid design and development within a user-centered design framework and to provide context by synthesizing reports of user-centered design applied to other personal health tools.
Methods:
We included articles describing at least one development step of 1) a patient decision aid, 2) user- or human-centered design of another personal health tool, or 3) evaluation of these. We organized data within a user-centered design framework comprising 3 elements in iterative cycles: understanding users, developing/refining prototype, and observing users.
Results:
We included 607 articles describing 325 patient decision aid projects and 65 other personal health tool projects. Fifty percent of patient decision aid projects reported involving users in at least 1 step for understanding users, 35% in at least 1 step for developing/refining the prototype, and 84% in at least 1 step for observing users' interaction with the prototype. In comparison, other personal health tool projects reported 91%, 49%, and 92%, respectively. A total of 74% of patient decision aid projects and 92% of other personal health tool projects reported iterative processes, both with a median of 3 iterative cycles. Preliminary evaluations such as usability or feasibility testing were reported in 66% of patient decision aid projects and 89% of other personal health tool projects.
Conclusions:
By synthesizing design and development practices, we offer evidence-based portraits of user involvement. Those wishing to further align patient decision aid design and development with user-centered design methods could involve users earlier, design and develop iteratively, and report processes in greater detail.
Background
Consent for data research in acute and critical care is complex as patients become at least temporarily incapacitated or die. Existing guidelines and regulations in the European Union are of limited help and there is a lack of literature about the use of data from this vulnerable group. To aid the creation of a patient-centred framework for responsible data research in the acute setting, we explored views of patients and next-of-kin about the collection, storage, sharing and use of genetic and health-related data for observational research.
Methods
We conducted qualitative interviews (n = 19) with Dutch sudden cardiac arrest survivors who donated clinical and socio-economic data and genetic samples to research. We also interviewed their next-of-kin. Topics were informed by ethics literature and we used scenario-sketches to aid discussion of complex issues.
Results
Sudden cardiac arrest survivors displayed limited awareness of their involvement in health data research and of the content of their given consent. We found that preferences regarding disclosure of clinically actionable genetic findings could change over time. When data collection and use were limited to the medical realm, patients trusted researchers to handle data responsibly without concern for privacy or other risks. There was no consensus as to whether deferred consent should be explicitly asked from survivors. If consent is asked, this would ideally be done a few months after the event when cognitive capacities have been regained. Views were divided about the need to obtain proxy consent for research with deceased patients’ data. However, there was general support for the disclosure of potentially relevant post-mortem genetic findings to relatives.
Conclusions
Sudden cardiac arrest patients’ donation of data for research was grounded in trust in medicine overall, blurring the boundary between research and care. Our findings also highlight questions about the acceptability of a one-time consent and about responsibilities of patients, researchers and ethics committees. Finally, further normative investigation is needed regarding the (continued) use of participants’ data after death, which is of particular importance in this setting. Our findings are thought to be of relevance for other acute and life-threatening illnesses as well.
Background
We aimed to examine the ethical concerns Singaporeans have about sharing health-data for precision medicine (PM) and identify suggestions for governance strategies. Just as Asian genomes are under-represented in PM, the views of Asian populations about the risks and benefits of data sharing are under-represented in prior attitudinal research.
Methods
We conducted seven focus groups with 62 participants in Singapore from May to July 2019. They were conducted in three languages (English, Mandarin and Malay) and analysed with qualitative content and thematic analysis.
Results
Four key themes emerged: nuanced understandings of data security and data sensitivity; trade-offs between data protection and research benefits; trust (and distrust) in the public and private sectors; and governance and control options. Participants were aware of the inherent risks associated with data sharing for research. Participants expressed conditional support for data sharing, including genomic sequence data and information contained within electronic medical records. This support included sharing data with researchers from universities and healthcare institutions, both in Singapore and overseas. Support was conditional on the perceived social value of the research and appropriate de-identification and data security processes. Participants suggested that a data sharing oversight body would help strengthen public trust and comfort in data research for PM in Singapore.
Conclusion
Maintenance of public trust in data security systems and governance regimes can enhance participation in PM and data sharing for research. Contrary to themes in much prior research, participants demonstrated a sophisticated understanding of the inherent risks of data sharing, analysed trade-offs between risks and potential benefits of PM, and often adopted an international perspective.
Objectives
Given widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data in AI research.
Design
A qualitative study involving six focus groups with members of the public. Participants discussed their views about AI in general, then were asked to share their thoughts about three realistic health AI research scenarios. Data were analysed using qualitative description thematic analysis.
Settings
Two cities in Ontario, Canada: Sudbury (400 km north of Toronto) and Mississauga (part of the Greater Toronto Area).
Participants
Forty-one purposively sampled members of the public (21M:20F, 25–65 years, median age 40).
Results
Participants had low levels of prior knowledge of AI and mixed, mostly negative, perceptions of AI in general. Most endorsed using data for health AI research when there is strong potential for public benefit, providing that concerns about privacy, commercial motives and other risks were addressed. Inductive thematic analysis identified AI-specific hopes (eg, potential for faster and more accurate analyses, ability to use more data), fears (eg, loss of human touch, skill depreciation from over-reliance on machines) and conditions (eg, human verification of computer-aided decisions, transparency). There were mixed views about whether data subject consent is required for health AI research, with most participants wanting to know if, how and by whom their data were used. Though it was not an objective of the study, realistic health AI scenarios were found to have an educational effect.
Conclusions
Notwithstanding concerns and limited knowledge about AI in general, most members of the general public in six focus groups in Ontario, Canada perceived benefits from health AI and conditionally supported the use of health data for AI research.
Objectives
: Denmark has invested a lot in the branding of its health data landscape as a role model. We explored to which extent this holds true, with a focus on data access for secondary uses and research, to also see what other countries can learn from the Danish experience.
Methods
: Semi-structured interviews were conducted with 15 Danish stakeholders working as policy makers, researchers or in public administration and having experience with the health data landscape. The transcripts underwent Qualitative Analysis following the QUAGOL framework.
Results
: The analysis focused on three themes:(i) the Danish health data landscape is considered very effective, but also features limitations regarding the secondary use of data, especially for collaborations with industry and international stakeholders;(ii) the development of institutional structures and the attitude of the Danish population towards data are intertwined with historical and cultural factors, limiting the possibility to emulate the Danish data landscape elsewhere; and(iii) technological advancements might hold challenges for the future sustainability of the Danish data landscape.
Conclusions
: The Danish model, although often branded as ideal, also relies on a balance between extensive data usage and persisting limitations. Hence, it should not be considered a ‘dream’ system to blindly emulate, but a valuable example of how such balance can be found, without forgetting that the latter requires continuous adaptation. Since the willingness of a population to approve of data usage may change due to privacy concerns, regular political renegotiations of the ethical underpinning of any health data landscape are crucial for their sustainability.
The Aotearoa New Zealand Integrated Data Infrastructure (IDI) is a national database containing a wide range of data about people and households. There is limited information about public views regarding its use for research.
A qualitative study was undertaken to examine the views of forty individuals attending a large hospital in Auckland, including those of Māori ethnicity and young people. Semi-structured interview data were analysed using Braun and Clarke's method of thematic analysis.
Seven key themes emerged: 1) Limited knowledge about medical data held in national databases; 2) Conditional support for the use of the IDI, including for research; 3) Concerns regarding the misuse of IDI data; 4) The importance of privacy; 5) Different views regarding consent for use of data for research; 6) Desire for access to personal data and the results of research; and 7) Concerns regarding third party and commercial use. Young people and those of Māori ethnicity were more wary of data misuse than others.
Although there is reasonable support for the secondary use of public administrative data in the IDI for research, there is more work to be done to ensure ethical and culturally appropriate use of this data via improved consent privacy management processes and researcher training.
Purpose
This study aims to provide a picture of the current state of art in the use of big data for decision-making processes for the management of health-care organizations.
Design/methodology/approach
A systematic literature review was carried out. The research uses two analyses: descriptive analysis, describing the evolution of citations; keywords; and the ten most influential papers, and bibliometric analysis, for content evaluation, for which a cluster analysis was performed.
Findings
A total of 48 articles were selected for bibliographic coupling out of an initial sample of more than 5,000 papers. Of the 48 articles, 29 are linked on the basis of their bibliography. Clustering the 29 articles on the basis of actual content, four research areas emerged: quality of care, quality of service, crisis management and data management.
Originality/value
Health-care organizations believe strongly that big data can become the most effective tool for correctly influencing the decision-making processes. Thus, more and more organizations continue to invest in big data analytics, and the literature on this topic has expanded rapidly. This study seeks to provide a comprehensive picture of the different streams of literature existing, together with gaps in research and future perspectives. The literature is mature enough for an analysis to be made and provide managers with useful insights on opportunities, criticisms and perspectives on the use of big data for health-care organizations. However, to date, there is no comprehensive literature review on the big data analysis in health care. Furthermore, as big data is a “sexy catchphrase,” more clarity on its usage may be needed. It represents an important tool to be investigated and its great potential is often yet to be discovered. This study thus sheds light on emerging issues and suggests further research that may be needed.
Background:
This study examines rural patients' perceived importance of knowing or being consulted about researchers' access and use of their personal data (identifiable and de-identified health information, and identifiable and de-identified non-health information) across five scenarios. This study also examines their views on stewardship or governance of their personal information by researchers in their healthcare systems.
Methods:
We conducted a survey by mail. Data were analyzed using descriptive statistics. Multivariable regression analyses were conducted across each scenario and type of personal data with the same variables included in each model.
Results:
The majority of participants said it was "very important/absolutely essential" to know the purpose of the study, to be asked every time, and to know the policies governing researcher access and use of their identifiable health information. Just over two-thirds of respondents thought it "very important/absolutely essential" to know who serves on the data governance committee and to have a community member serve. Distrust in healthcare organizations was positively correlated with the scenarios while willingness to give permission to donate leftover biological specimens was negatively correlated.
Conclusion:
Our study findings indicate that the type of personal information being accessed and used generally matters to 1,407 patients living in rural Pennsylvania. We also demonstrate that knowing their healthcare organizations' governance policies and practices for managing their personal data is important to many rural Pennsylvania patients. Biomedical researchers need to recognize and attend to those differences as much as possible in order to expand opportunities for and participation in research by residents of these rural communities.
Supplemental data for this article is available online at.
Introduction
The governance structures associated with health data are evolving in response to advances in digital technologies that enable new ways of capturing, using, and sharing different types of data. Increasingly, health data moves between different contexts such as from healthcare to research, or to commerce and marketing. Crossing these contextual boundaries has the potential to violate societal expectations about the appropriate use of health data and diminish public trust. Understanding citizens’ views on the acceptability of and preferences for data use in different contexts is essential for developing information governance policies in these new contexts.
Methods
Focus group design presenting data sharing scenarios in England, Iceland, and Sweden.
Results
Seventy-one participants were recruited. Participants supported the need for data to help understand the observable world, improve medical research, the quality of public services, and to benefit society. However, participants consistently identified the lack of information, transparency and control as barriers to trusting organisations to use data in a way that they considered appropriate. There was considerable support for fair and transparent data sharing practices where all parties benefitted.
Conclusion
Data governance policy should involve all stakeholders’ perspectives on an ongoing basis, to inform and implement changes to health data sharing practices that accord with stakeholder views. The Findings showed that 1) data should be used for ethical purposes even when there was commercial interest; 2) data subjects and/or public institutions that provide and share data should also receive benefits from the sharing of data; 3) third parties use of data requires greater transparency and accountability than currently exists, 4) there should be greater information provided to empower data subjects.
Health care providers are increasingly providing technologies for patient care; however, patients are still loath to use such technologies consistently. This research examines the impediments to patients' use of e-health portals. Our analysis of 836 data records showed that while privacy and security concerns have a negative impact on attitudes toward e-health portals, increasing the awareness of privacy and security controls alleviates such concerns. Our findings also suggest that individuals worry more about who possesses the right to access their health data (i.e., who, what, when, and why) than the mechanisms used to safeguard data from unauthorized access. We found that perceived benefits and support (i.e., emotional and technical support) positively influenced the determinants of use intentions. The implications of these findings for health care providers and policy makers are discussed.
[Motivation] Artificial intelligence (AI) creates many opportunities for public institutions, but the unethical use of AI in public services can reduce citizens’ trust. [Question] The aim of this study was to identify what kind of requirements citizens have for trustworthy AI services in the public sector. The study included 21 interviews and a design workshop of four public AI services. [Results] The main finding was that all the participants wanted public AI services to be transparent. This transparency requirement covers a number of questions that trustworthy AI services must answer, such as about their purposes. The participants also asked about the data used in AI services and from what sources the data were collected. They pointed out that AI must provide easy-to-understand explanations. We also distinguished two other important requirements: controlling personal data usage and involving humans in AI services. [Contribution] For practitioners, the paper provides a list of questions that trustworthy public AI services should answer. For the research community, it illuminates the transparency requirement of AI systems from the perspective of citizens.
Research utilising de-identified patient health information extracted from electronic medical records (EMRs) from general practices has steadily grown in recent years in response to calls to increase use of health data for research and other secondary purposes in Australia. Little is known about the views of key primary care personnel on this issue, which are important, as they may influence whether practices agree to provide EMR data for research. This exploratory qualitative study investigated the attitudes and beliefs of general practitioners (GPs), practice managers (PMs) and practice nurses (PNs) around sharing de-identified EMR patient health information with researchers. Semi-structured interviews were conducted with 11 participants (6 GPs, 3 PMs and 2 PNs) recruited via purposive sampling from general practices in Victoria, Australia. Transcripts were coded and thematically analysed. Participants were generally enthusiastic about research utilising de-identified health information extracted from EMRs for altruistic reasons, including: positive effects on primary care research, clinical practice and population health outcomes. Concerns raised included patient privacy and data breaches, third-party use of extracted data and patient consent. These findings can provide guidance to researchers and policymakers in designing and implementing projects involving de-identified health information extracted from EMRs.