Health Data For Research Purposes Research Articles

Protection of Personal Data in Telemedicine

The protection of personal data in telemedicine in the context of current legislation and regulatory acts of the European Union is considered. Social relations in the field of use of personal data in telemedicine are studied, in particular, legal regulation of the use of personal data processed in health care information systems. In the information society, the right to health care and medical care is closely related to the right to access information. The right to access to information is a guarantee of the exercise of the right to health care and medical care, defines its content and contributes to equal access of every person to medical care. It is indicated that ensuring the balance of private and public interests in telemedicine requires differentiation of the conditions for processing personal health data. As an additional condition for the processing of personal data for specific purposes, it is proposed to provide for the consent of the subject of personal data to data processing with the right to refuse processing. Such purposes may include, in particular, the processing of electronic health records in the unified state health information system, the processing of depersonalized personal health data for research purposes. This approach contributes to the protection of public interests in health care and takes into account the autonomy of the will of the subject of personal data, his interests in the field of personal information security, corresponds to approaches to legal regulation in the European Union.

Public Attitudes Towards Access to Health Data for Research Purposes Through Citizens' Jury in Uganda.

Citizens juries (CJ) are a method of deliberative action research that have been utilized in countries with well-funded health care systems to address questions about access to health data. Uganda is classified as a low-income country and utilizes a predominantly paper-based health record system. The burgeoning electronic health record in the central area represents an opportunity to collect and analyze longitudinal data on patients living with long term HIV infection and multiple diseases, a hitherto unexplored disease mapping exercise We set out to understand the public perception towards the use of data for research purposes such as this among Ugandans utilizing an adapted strategy sensitive to the local culture. The jury were unanimous that electronic data should be used for research provided certain safeguards are adhered to and most importantly, that consent to do so is obtained on the basis of a clear rationale for the project.

What are the bottlenecks to health data sharing in Switzerland? An interview study.

While health data sharing for research purposes is strongly supported in principle, it can be challenging to implement in practice. Little is known about the actual bottlenecks to health data sharing in Switzerland. This study aimed to assess the obstacles to Swiss health data sharing, including legal, ethical and logistical bottlenecks. We identified 37 key stakeholders in data sharing via the Swiss Personalised Health Network ecosystem, defined as being an expert on sharing sensitive health data for research purposes at a Swiss university hospital (or a Swiss disease cohort) or being a stakeholder in data sharing at a public or private institution that uses such data. We conducted semi-structured interviews, which were transcribed, translated when necessary, and de-identified. The entire research team discussed the transcripts and notes taken during each interview before an inductive coding process occurred. Eleven semi-structured interviews were conducted (primarily in English) with 17 individuals representing lawyers, data protection officers, ethics committee members, scientists, project managers, bioinformaticians, clinical trials unit members, and biobank stakeholders. Most respondents felt that it was not the actual data transfer that was the bottleneck but rather the processes and systems around it, which were considered time-intensive and confusing. The templates developed by the Swiss Personalised Health Network and the Swiss General Consent process were generally felt to have streamlined processes significantly. However, these logistics and data quality issues remain practical bottlenecks in Swiss health data sharing. Areas of legal uncertainty include privacy laws when sharing data internationally, questions of "who owns the data", inconsistencies created because the Swiss general consent is perceived as being implemented differently across different institutions, and definitions and operationalisation of anonymisation and pseudo-anonymisation. Many participants desired to create a "culture of data sharing" and to recognise that data sharing is a process with many steps, not an event, that requires sustainability efforts and personnel. Some participants also stressed a desire to move away from data sharing and the current privacy focus towards processes that facilitate data access. Facilitating a data access culture in Switzerland may require legal clarifications, further education about the process and resources to support data sharing, and further investment in sustainable infrastructureby funders and institutions.

Wissen und Einstellung zur Speicherung und Nutzung von Gesundheitsdaten: Ergebnisse einer Bevölkerungsbefragung

ObjectiveThe article tackles various issues arising in the context of the process of digitalization in the health sector. The communication and availability of health data, health registers, the electronic health record, consent procedures for the transfer of data and access to health data for research are considered. MethodsThe study is based on a computer-assisted telephone survey (dual-frame) of a random sample of adult people living in Germany. Data was collected in the period between June 01 and June 27, 2022 (n = 1,308). ResultsThe level of knowledge concerning the transmission of health data to health insurers is good, whereas the existence of central death-, vaccination- and health registers as well as the access to health data by treating physicians is overestimated. The general acceptance of medical registers is very high. Half the population is unfamiliar with the electronic health record, and the willingness to use it is rather low. An opt-in procedure is preferred when transferring data, and more than eighty percent would release data in their electronic health file for research purposes. Three quarters would consent that their health data be handed over to general research, especially if reserach facilities were situated at German universities, under the condition that their data be treated confidentiallly. The willingness to release data correlates with the level of trust in the press as well as in universities and colleges and decreases when a data leak is considered to be serious. Discussion and conclusionIn Germany, as in other European countries, we observe a great willingness of people to release health data for research purposes. However, the propensity to use the electronic health file is comparatively low, as is the acceptance of an opt-out procedure, which in the literature is considered a prerequisite for the successful implementation of electronic health records in other countries. Unsurprisingly, a general trust in research and government agencies that process health data is a key factor.

Views on sharing mental health data for research purposes: qualitative analysis of interviews with people with mental illness

BackgroundImproving the ways in which routinely-collected mental health data are shared could facilitate substantial advances in research and treatment. However, this process should only be undertaken in partnership with those who provide such data. Despite relatively widespread investigation of public perspectives on health data sharing more generally, there is a lack of research on the views of people with mental illness.MethodsTwelve people with lived experience of mental illness took part in semi-structured interviews via online video software. Participants had experience of a broad range of mental health conditions including anxiety, depression, schizophrenia, eating disorders and addiction. Interview questions sought to establish how participants felt about the use of routinely-collected health data for research purposes, covering different types of health data, what health data should be used for, and any concerns around its use.ResultsThematic analysis identified four overarching themes: benefits of sharing mental health data, concerns about sharing mental health data, safeguards, and data types. Participants were clear that health data sharing should facilitate improved scientific knowledge and better treatments for mental illness. There were concerns that data misuse could become another way in which individuals and society discriminate against people with mental illness, for example through insurance premiums or employment decisions. Despite this there was a generally positive attitude to sharing mental health data as long as appropriate safeguards were in place.ConclusionsThere was notable strength of feeling across participants that more should be done to reduce the suffering caused by mental illness, and that this could be partly facilitated by well-managed sharing of health data. The mental health research community could build on this generally positive attitude to mental health data sharing by following rigorous best practice tailored to the specific concerns of people with mental illness.

Conceptualizing fairness in the secondary use of health data for research: A scoping review

ABSTRACT With the introduction of the European Health Data Space (EHDS), the secondary use of health data for research purposes is attracting more attention. Secondary health data processing promises to address novel research questions, inform the design of future research and improve healthcare delivery generally. To comply with the existing data protection regulations, the secondary data use must be fair, among other things. However, there is no clear understanding of what fairness means in the context of secondary use of health data for scientific research purposes. In response, we conducted a scoping review of argument-based literature to explore how fairness in the secondary use of health data has been conceptualized. A total of 35 publications were included in the final synthesis after abstract and full-text screening. Using an inductive approach and a thematic analysis, our review has revealed that balancing individual and public interests, reducing power asymmetries, setting conditions for commercial involvement, and implementing benefit sharing are essential to guarantee fair secondary use research. The findings of this review can inform current and future research practices and policy development to adequately address concerns about fairness in the secondary use of health data.

Enhancing the reuse of health data for research purposes: laws and regulations as pillars of trust

Abstract Background Routinely recorded health data are increasingly used for research purposes and indispensable to stimulating appropriate and sustainable health care. In many countries access to data has proven to be a challenge. Trust by researchers, organisations and the general public is key, and adherence to the rule of law is one of the key elements determining that trust. We investigated the laws and regulations regarding the reuse of health data and how they work out practically for researchers. Methods Our study focuses on France, Finland, Denmark, Germany, England and The Netherlands. We investigated consent mechanisms, the possibilities of record linkage, and how the sharing of data for research purposes was organised, with a combination of desk research and interviews with researchers in these countries. Results All countries investigated except England are subject to the General Data Protection Regulation. However, explicit consent is the default in Germany and the Netherlands, while other countries maintain an opt-out system or even a system of neither consent nor opt-out. A central data access authority is in place in all countries investigated except Germany and the Netherlands. The nature and level of detail of data varies widely. Conclusions GDPR does not dictate a specific modality for the reuse of data. In terms of the reuse of health data, Germany and the Netherlands are lagging. The Netherlands seems to be the only country with continuing discussions about consent modalities. A broader societal debate about the balance between trust and the reuse of health data is needed, also against the background of a European Health Data Space. In the Netherlands, widespread government distrust is one of the challenges. Options to counteract this distrust will be discussed. Key messages • European countries vary in the way routine health data are accessible for research purposes. • This will affect the feasibility of a uniform European Health Data Space.

‘My Data’ project: Understanding the perceptions of administrative data usage for research of people who use drugs

ObjectivesAdministrative data research requires trust that data will be used sensitively and wisely. People who use drugs are frequently stigmatised, and trust may be a particular barrier. This project aims to understand the perceptions of people who use drugs around the use of their administrative health data for research purposes.
 MethodsThis project will work with Restoration Fife, a third-sector organisation based in Fife, Scotland, that supports people who use drugs. We are conducting focus groups exploring how administrative health data are used in research from the perspectives of people who use drugs, including discussion around different types/sources of data. Data will be analysed using the Framework approach. We will also work with an artist and members of Restoration Fife, to co-produce a short, animated film about how administrative data are used in research around drug use, in order to educate the wider population about how their data are used.
 Results*This presentation will discuss findings from the focus groups on the perceptions of usage of administrative data for different types of research. It will also discuss the use of administrative data in the context of findings from previous studies involving general populations and populations with other vulnerabilities, such as care-experienced populations and people with mental health difficulties. We will also provide a viewing of the film within this paper session.
 *This project is funded by Research Data Scotland and runs from April to September 2023: all results will therefore be available by the time of the ADR conference in November 2023.
 ConclusionsEvidence suggests low levels of public awareness of how and why data are used. We know little about perceptions of people who use drugs, for whom trust of services may be a particular issue. This study uses innovative methods to provide a platform for voices rarely heard in this context.

A comparison of synthetic data generation and federated analysis for enabling international evaluations of cardiovascular health

Sharing health data for research purposes across international jurisdictions has been a challenge due to privacy concerns. Two privacy enhancing technologies that can enable such sharing are synthetic data generation (SDG) and federated analysis, but their relative strengths and weaknesses have not been evaluated thus far. In this study we compared SDG with federated analysis to enable such international comparative studies. The objective of the analysis was to assess country-level differences in the role of sex on cardiovascular health (CVH) using a pooled dataset of Canadian and Austrian individuals. The Canadian data was synthesized and sent to the Austrian team for analysis. The utility of the pooled (synthetic Canadian + real Austrian) dataset was evaluated by comparing the regression results from the two approaches. The privacy of the Canadian synthetic data was assessed using a membership disclosure test which showed an F1 score of 0.001, indicating low privacy risk. The outcome variable of interest was CVH, calculated through a modified CANHEART index. The main and interaction effect parameter estimates of the federated and pooled analyses were consistent and directionally the same. It took approximately one month to set up the synthetic data generation platform and generate the synthetic data, whereas it took over 1.5 years to set up the federated analysis system. Synthetic data generation can be an efficient and effective tool for enabling multi-jurisdictional studies while addressing privacy concerns.

Healthcare utilization and unmet needs of patients with antisynthetase syndrome: An international patient survey

Antisynthease syndrome (ASSD) is a rare, complex and understudied autoimmune disease. Internet-based studies can overcome barriers of traditional on-site research and are therefore very appealing for rare diseases. The aim of this study was to investigate patient-reported symptoms, diagnostic delay, symptoms, medical care, health status, working status, disease knowledge and willingness to participate in research of ASSD patients by conducting an international web-based survey. The multilingual questionnaire was created by an international group of rheumatologists and patients and distributed online. 236 participants from 22 countries completed the survey. 184/236 (78.0%) were female, mean age (SD) was 49.6 years (11.3) and most common antisynthetase antibody was Jo-1 (169/236, 71.6%). 79/236 (33.5%) reported to work full-time. Median diagnostic delay was one year. The most common symptom at disease onset was fatigue 159/236 (67.4%), followed by myalgia 130/236 (55.1%). The complete triad of myositis, arthritis and lung involvement verified by a clinician was present in 42/236 (17.8%) at disease onset and in 88/236 (37.3%) during the disease course. 36/236 (15.3%) reported to have been diagnosed with fibromyalgia and 40/236 (16.3%) with depression. The most reported immunosuppressive treatments were oral corticosteroids 179/236 (75.9%), followed by rituximab 85/236 (36.0%). 73/236 (30.9%) had received physiotherapy treatment. 71/236 (30.1%) reported to know useful online information sources related to ASSD. 223/236 (94.5%) were willing to share health data for research purposes once a year. Our results reiterate that internet-based research is invaluable for cooperating with patients to foster knowledge in rare diseases.

MINDER Smart home test bed site – embedding dementia research into primary health and social care. Wingfield, D. Daniels, S. Norman, C. Lai, H. Hassim, N. Nilforooshan, R. Barnarghi, P. Sharp, D

AbstractBackgroundDigitally enabled healthcare is becoming mainstream NHS (1) and adoption has been accelerated in response to the COVID‐19 pandemic (2) The UK Dementia Research Institute Care Research & Technology Centre, established in 2019, explores the value of using technology in people’s homes to improve care and has developed a system (MINDER) using IOT/smart home technology and medical devices, integrating activity and health data for research purposes and generating health alerts to the mainstream provider via a clinical monitoring team. Initially launched in Surrey and Borders Partnership NHS Trust (n = 40); in April 2021, an additional research site was established within primary care in North West London.MethodWe collated data from both sites and describe an integrated delivery model for research within primary health and social care. Cohort description and case studies illustrate the challenges and benefits of conducting this research across urban and sub‐urban settings.ResultsOver 55 participants are currently enrolled on the study. 15 of these from primary care/general practice in the London Borough of Hammersmith and Fulham. Opportunities arising from this setting include leveraging the patient – provider (nurse/doctor/allied health professional/social care) relationship to introduce the study and recruit, and rapid escalation of any problems arising in a research context to the clinical/care teams responsible to delivering care (for example; potential urinary tract infections). Challenges to recruitment have included lack of specialist confirmation of dementia diagnosis in primary care records, lack of consistent engagement/availability of the required MINDER study partner as well as the impact of the COVID 19 pandemic limited face to face contact.ConclusionEarly data suggests that a complex dementia study can be embedded successfully in General Practice and leads to strengthening of relations with care giving bodies. This offers the opportunity for development and translation of new technologies within front line primary and social care, that can be fully evaluated within the real world context of service delivery.References 1)The NHS Long Term Plan (2019) gov.uk 2) Baird B, Maguire D. Understanding factors that enabled digital service change in general practice during the Covid‐19 pandemic. London: The King’s Fund. 2021 Feb.

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

Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness. We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations. Using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using Medline, CINAHL, PsycINFO, Scopus, Cochrane Library, and PubMed databases to locate a broad range of studies published in English or French until November 2022. We included articles reporting a stakeholder's perspective or recommendations of what information patients and members of the public want to learn about the secondary use of health data for research purposes and how or in which situations. Data were collected and analyzed with an iterative thematic approach using NVivo. Overall, 178 articles were included in this scoping review. The type of information can be divided into generic and specific content. Generic content includes information on governance and regulatory frameworks, technical aspects, and scientific aims. Specific content includes updates on the use of one's data, return of results from individual tests, information on global results, information on data sharing, and how to access one's data. Recommendations on how to communicate the information focused on frequency, use of various supports, formats, and wording. Methods for communication generally favored broad approaches such as nationwide publicity campaigns, mainstream and social media for generic content, and mixed approaches for specific content including websites, patient portals, and face-to-face encounters. Content should be tailored to the individual as much as possible with regard to length, avoidance of technical terms, cultural competence, and level of detail. Finally, the review outlined 4 major situations where communication was deemed necessary: before a new use of data, when new test results became available, when global research results were released, and in the advent of a breach in confidentiality. This review highlights how different types of information and approaches to communication efforts may serve as the basis for achieving greater transparency. Governing bodies could use the results: to elaborate or evaluate strategies to educate on the potential benefits; to provide some knowledge and control over data use as a form of reciprocity; and as a condition to engage citizens and build and maintain trust. Future work is needed to assess which strategies achieve the greatest outreach while striking a balance between meeting information needs and use of resources.

A method for generating synthetic longitudinal health data

Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative health data would be to share synthetic datasets where the records do not correspond to real individuals, but the patterns and relationships seen in the data are reproduced. This paper assesses the feasibility of generating synthetic administrative health data using a recurrent deep learning model. Our data comes from 120,000 individuals from Alberta Health’s administrative health database. We assess how similar our synthetic data is to the real data using utility assessments that assess the structure and general patterns in the data as well as by recreating a specific analysis in the real data commonly applied to this type of administrative health data. We also assess the privacy risks associated with the use of this synthetic dataset. Generic utility assessments that used Hellinger distance to quantify the difference in distributions between real and synthetic datasets for event types (0.027), attributes (mean 0.0417), Markov transition matrices (order 1 mean absolute difference: 0.0896, sd: 0.159; order 2: mean Hellinger distance 0.2195, sd: 0.2724), the Hellinger distance between the joint distributions was 0.352, and the similarity of random cohorts generated from real and synthetic data had a mean Hellinger distance of 0.3 and mean Euclidean distance of 0.064, indicating small differences between the distributions in the real data and the synthetic data. By applying a realistic analysis to both real and synthetic datasets, Cox regression hazard ratios achieved a mean confidence interval overlap of 68% for adjusted hazard ratios among 5 key outcomes of interest, indicating synthetic data produces similar analytic results to real data. The privacy assessment concluded that the attribution disclosure risk associated with this synthetic dataset was substantially less than the typical 0.09 acceptable risk threshold. Based on these metrics our results show that our synthetic data is suitably similar to the real data and could be shared for research purposes thereby alleviating concerns associated with the sharing of real data in some circumstances.

FAIRification of health-related data using semantic web technologies in the Swiss Personalized Health Network

The Swiss Personalized Health Network (SPHN) is a government-funded initiative developing federated infrastructures for a responsible and efficient secondary use of health data for research purposes in compliance with the FAIR principles (Findable, Accessible, Interoperable and Reusable). We built a common standard infrastructure with a fit-for-purpose strategy to bring together health-related data and ease the work of both data providers to supply data in a standard manner and researchers by enhancing the quality of the collected data. As a result, the SPHN Resource Description Framework (RDF) schema was implemented together with a data ecosystem that encompasses data integration, validation tools, analysis helpers, training and documentation for representing health metadata and data in a consistent manner and reaching nationwide data interoperability goals. Data providers can now efficiently deliver several types of health data in a standardised and interoperable way while a high degree of flexibility is granted for the various demands of individual research projects. Researchers in Switzerland have access to FAIR health data for further use in RDF triplestores.

Innovative Methods Used in Monitoring COVID-19 in Europe: A Multinational Study.

Several innovative methods have been deployed worldwide to curb the COVID-19 pandemic. The aim of the study is to investigate which innovative methods are used to monitor COVID-19 health issues in Europe and related legislative and ethical aspects. An online questionnaire was administered to European countries' representatives of the project Population Health Information Research Infrastructure. Additional information was obtained from websites and documents provided by the respondents; an overview of the literature was also performed. Respondents from 14 countries participated in the study. Digital tools are used to monitor the spread of COVID-19 (13/14 countries) and vaccination coverage (12/14); for research, diagnostics, telehealth (14/14); to fight disinformation (11/14) and forecast the pandemic spread (4/14). The level of implementation of telehealth applications was mostly low/medium. Legislative and ethical issues were encountered in many countries, leading to institutional distrust. The COVID-19 pandemic has highlighted the need for timely and accurate health data for research purposes and policy planning. However, the use of innovative methods for population health monitoring and timely data collection has posed challenges to privacy and online security globally. Adequate regulatory oversight, targeted public health interventions, and fight against disinformation could improve the uptake rate and enhance countries' emergency preparedness.

Practices and Attitudes of Bavarian Stakeholders Regarding the Secondary Use of Health Data for Research Purposes During the COVID-19 Pandemic: Qualitative Interview Study.

BackgroundThe COVID-19 pandemic is a threat to global health and requires collaborative health research efforts across organizations and countries to address it. Although routinely collected digital health data are a valuable source of information for researchers, benefiting from these data requires accessing and sharing the data. Health care organizations focusing on individual risk minimization threaten to undermine COVID-19 research efforts, and it has been argued that there is an ethical obligation to use the European Union’s General Data Protection Regulation (GDPR) scientific research exemption during the COVID-19 pandemic to support collaborative health research.ObjectiveThis study aims to explore the practices and attitudes of stakeholders in the German federal state of Bavaria regarding the secondary use of health data for research purposes during the COVID-19 pandemic, with a specific focus on the GDPR scientific research exemption.MethodsIndividual semistructured qualitative interviews were conducted between December 2020 and January 2021 with a purposive sample of 17 stakeholders from 3 different groups in Bavaria: researchers involved in COVID-19 research (n=5, 29%), data protection officers (n=6, 35%), and research ethics committee representatives (n=6, 35%). The transcripts were analyzed using conventional content analysis.ResultsParticipants identified systemic challenges in conducting collaborative secondary-use health data research in Bavaria; secondary health data research generally only happens when patient consent has been obtained, or the data have been fully anonymized. The GDPR research exemption has not played a significant role during the pandemic and is currently seldom and restrictively used. Participants identified 3 key groups of barriers that led to difficulties: the wider ecosystem at many Bavarian health care organizations, legal uncertainty that leads to risk-adverse approaches, and ethical positions that patient consent ought to be obtained whenever possible to respect patient autonomy. To improve health data research in Bavaria and across Germany, participants wanted greater legal certainty regarding the use of pseudonymized data for research purposes without the patient’s consent.ConclusionsThe current balance between enabling the positive goals of health data research and avoiding associated data protection risks is heavily skewed toward avoiding risks; so much so that it makes reaching the goals of health data research extremely difficult. This is important, as it is widely recognized that there is an ethical imperative to use health data to improve care. The current approach also creates a problematic conflict with the ambitions of Germany, and the federal state of Bavaria, to be a leader in artificial intelligence. A recent development in the field of German public administration known as norm screening (Normenscreening) could potentially provide a systematic approach to minimize legal barriers. This approach would likely be beneficial to other countries.

Experience of clinical services shapes attitudes to mental health data sharing: findings from a UK-wide survey

BackgroundRoutinely-collected mental health data could deliver novel insights for mental health research. However, patients’ willingness to share their mental health data remains largely unknown. We investigated factors influencing likelihood of sharing these data for research purposes amongst people with and without experience of mental illness.MethodsWe collected responses from a diverse sample of UK National Health Service (NHS) users (n = 2187) of which about half (n = 1087) had lifetime experience of mental illness. Ordinal logistic regression was used to examine the influence of demographic factors, clinical service experience, and primary mental illness on willingness to share mental health data, contrasted against physical health data.ResultsThere was a high level of willingness to share mental (89.7%) and physical (92.8%) health data for research purposes. Higher levels of satisfaction with the NHS were associated with greater willingness to share mental health data. Furthermore, people with personal experience of mental illness were more willing than those without to share mental health data, once the variable of NHS satisfaction had been controlled for. Of the mental illnesses recorded, people with depression, obsessive-compulsive disorder (OCD), personality disorder or bipolar disorder were significantly more likely to share their mental health data than people without mental illness.ConclusionsThese findings suggest that positive experiences of health services and personal experience of mental illness are associated with greater willingness to share mental health data. NHS satisfaction is a potentially modifiable factor that could foster public support for increased use of NHS mental health data in research.

Verkn\xfcpfung von Abrechnungsdaten gesetzlicher Krankenkassen mit Daten epidemiologischer Krebsregister: l\xe4nderspezifische M\xf6glichkeiten und Limitationen

ZusammenfassungHintergrundIn den letzten Jahren wird verstärkt gefordert, Forschungsdaten gemäß den sog. FAIR-Prinzipien für eine Nachnutzung aufzubereiten. Dadurch könnten zukünftige Projekte auf einer breiteren Datengrundlage durchgeführt sowie durch Verknüpfung verschiedener Datenquellen neue Fragestellungen untersucht werden.FragestellungEruiert werden soll, inwieweit Abrechnungsdaten gesetzlicher Krankenversicherungen mit den Daten der Landeskrebsregister (LKR) überregional verknüpft werden können, um die in den Abrechnungsdaten fehlenden Informationen zu Krebserkrankungen ergänzen und die Validität der dortigen Angaben zur Tumordiagnose beurteilen zu können. Der Fokus liegt dabei auf der Beschreibung der länderspezifischen Anforderungen für einen solchen Datenabgleich.Material und MethodenAls Datenquellen wurden die Pharmakoepidemiologische Forschungsdatenbank GePaRD des Leibniz-Instituts für Präventionsforschung und Epidemiologie – BIPS und sechs Krebsregister herangezogen. Zur Verknüpfung wurden vergleichend das logistisch aufwendige direkte Linkage- und ein weniger aufwendiges indirektes Linkage-Verfahren angewandt. Dazu mussten für GePaRD und für jedes LKR die Genehmigungen der jeweils zuständigen Behörde eingeholt werden.ErgebnisseHinsichtlich der Verknüpfung von LKR-Daten mit GePaRD zeigten sich gravierende Unterschiede in der Datenbereitstellung (vollständige Ablehnung bis hin zu einer unkomplizierten Umsetzung).DiskussionIn Deutschland müssen einheitliche Rahmenbedingungen geschaffen werden, um eine angemessene Nachnutzung und eine Verknüpfung von personenbezogenen Gesundheitsdaten zu Forschungszwecken im Sinne der FAIR-Prinzipien zu ermöglichen. Bezüglich der Verknüpfung von LKR-Daten mit anderen Datenquellen könnte das neue Gesetz zur Zusammenführung von Krebsregisterdaten Abhilfe schaffen.

What Can We Do with the Data of Deceased People? A Normative Proposal

The health and genetic data of deceased people are a particularly important asset in the field of biomedical research. However, in practice, using them is complicated, as the legal framework that should regulate their use has not been fully developed yet. The General Data Protection Regulation (GDPR) is not applicable to such data and the Member States have not been able to agree on an alternative regulation. Recently, normative models have been proposed in an attempt to face this issue. The most wellknown of these is posthumous medical data donation (PMDD). This proposal supports an opt-in donation system of health data for research purposes. In this article, we argue that PMDD is not a useful model for addressing the issue at hand, as it does not consider that some of these data (the genetic data) may be the personal data of the living relatives of the deceased. Furthermore, we find the reasons supporting an opt-in model less convincing than those that vouch for alternative systems. Indeed, we propose a normative framework that is based on the opt-out system for non-personal data combined with the application of the GDPR to the relatives’ personal data.

A Social Media Campaign (#datasaveslives) to Promote the Benefits of Using Health Data for Research Purposes: Mixed Methods Analysis.

BackgroundSocial media provides the potential to engage a wide audience about scientific research, including the public. However, little empirical research exists to guide health scientists regarding what works and how to optimize impact. We examined the social media campaign #datasaveslives established in 2014 to highlight positive examples of the use and reuse of health data in research.ObjectiveThis study aims to examine how the #datasaveslives hashtag was used on social media, how often, and by whom; thus, we aim to provide insights into the impact of a major social media campaign in the UK health informatics research community and further afield.MethodsWe analyzed all publicly available posts (tweets) that included the hashtag #datasaveslives (N=13,895) on the microblogging platform Twitter between September 1, 2016, and August 31, 2017. Using a combination of qualitative and quantitative analyses, we determined the frequency and purpose of tweets. Social network analysis was used to analyze and visualize tweet sharing (retweet) networks among hashtag users.ResultsOverall, we found 4175 original posts and 9720 retweets featuring #datasaveslives by 3649 unique Twitter users. In total, 66.01% (2756/4175) of the original posts were retweeted at least once. Higher frequencies of tweets were observed during the weeks of prominent policy publications, popular conferences, and public engagement events. Cluster analysis based on retweet relationships revealed an interconnected series of groups of #datasaveslives users in academia, health services and policy, and charities and patient networks. Thematic analysis of tweets showed that #datasaveslives was used for a broader range of purposes than indexing information, including event reporting, encouraging participation and action, and showing personal support for data sharing.ConclusionsThis study shows that a hashtag-based social media campaign was effective in encouraging a wide audience of stakeholders to disseminate positive examples of health research. Furthermore, the findings suggest that the campaign supported community building and bridging practices within and between the interdisciplinary sectors related to the field of health data science and encouraged individuals to demonstrate personal support for sharing health data.