Novel and Proven Models of Public, Private, and Public-Private Partnerships in Healthcare: An Update.

Initiatives to share assets in the life science sector through dedicated partnerships had and still have a multitude of different aspects in the past few decades. The range goes from industry partners, small and big companies, in bilateral agreements with academic institutions up to large privately and publicly funded consortia. In general, the term public-private partnership (PPP) is used when at least one public (non-profit, academic, and/or government) part and one or more private for-profit partners are involved. A Public-Private Partnership is often driven by a public body, i.e. a ministry or a public agency. Their synergism has been described 10 years ago (Dearing, Science 315(19):344-347, 2007; Casty and Wieman, Ther Innov Regul Sci 47(3):375-383, 2013; Stevens et al., Biotechnol Law Rep 34(4):153-165, 2015). So why view this synergism again today? It will be shown that the situation in life science has changed: novel partners acting digital, data expertise being involved on many levels and novel partnering models arising. Success and challenges will be described in this chapter.

[Nationally standardized broad consent in practice: initial experiences, current developments, and critical assessment]. / National standardisierter Broad Consent in der Praxis: erste Erfahrungen, aktuelle Entwicklungen und kritische Betrachtungen.

BACKGROUND: The digitalization in the healthcare sector promises a secondary use of patient data in the sense of a learning healthcare system. For this, the Medical Informatics Initiative's (MII) Consent Working Group has created an ethical and legal basis with standardized consent documents. This paper describes the systematically monitored introduction of these documents at the MII sites. METHODS: The monitoring of the introduction included regular online surveys, an in-depth analysis of the introduction processes at selected sites, and an assessment of the documents in use. In addition, inquiries and feedback from a large number of stakeholders were evaluated. RESULTS: The online surveys showed that 27 of the 32 sites have gradually introduced the consent documents productively, with a current total of 173,289 consents. The analysis of the implementation procedures revealed heterogeneous organizational conditions at the sites. The requirements of various stakeholders were met by developing and providing supplementary versions of the consent documents and additional information materials. DISCUSSION: The introduction of the MII consent documents at the university hospitals creates a uniform legal basis for the secondary use of patient data. However, the comprehensive implementation within the sites remains challenging. Therefore, minimum requirements for patient information and supplementary recommendations for best practice must be developed. The further development of the national legal framework for research will not render the participation and transparency mechanisms developed here obsolete.

Harmonization after the GDPR? Divergences in the rules for genetic and health data sharing in four member states and ways to overcome them by EU measures: Insights from Germany, Greece, Latvia and Sweden.

The EU member states' healthcare and health-related research sectors are both characterized by an emerging infrastructural coalescence on a national and European level. The culmination of this coalescence is the planned creation of a European Health Data Space, an EU-wide infrastructure for the processing of personal data for healthcare and for secondary uses such as scientific research. In contrast to growing technical interoperability, the legal framework for such integration is not yet defined in detail, particularly with regard to data protection law. Its development is accompanied by discussions about divergent member state implementations of the EU General Data Protection Regulation (GDPR) that affect data sharing between healthcare and scientific research actors and across various sectors driven by divergent processing purposes. The article presents four member states' main rules on data sharing based on the respective provision of the GDPR in six health-related contexts regarding data sharing across the healthcare and research sector and between the main actors of those sectors. The striking differences are then evaluated from the perspective of their factual effect on European data sharing depending on the legal characteristics of the GDPR provisions they rely on. Against this backdrop, the planned regulatory measures for the setup of the European Health Data Space are introduced and evaluated with regard to further harmonization between member states' laws and possibilities to overcome divergences in data protection rules relevant for European data sharing. The results of the analysis point to the conclusion that the destructive effect of divergent member state rules depends on the legal qualification of the EU provisions they rely on and that this qualification also determines which further EU regulatory measure would be the most effective to set the framework for the European Health Data Space.

ISO 15189 is a sufficient instrument to guarantee high-quality manufacture of laboratory developed tests for in-house-use conform requirements of the European In-Vitro-Diagnostics Regulation.

The EU In-Vitro Diagnostic Device Regulation (IVDR) aims for transparent risk-and purpose-based validation of diagnostic devices, traceability of results to uniquely identified devices, and post-market surveillance. The IVDR regulates design, manufacture and putting into use of devices, but not medical services using these devices. In the absence of suitable commercial devices, the laboratory can resort to laboratory-developed tests (LDT) for in-house use. Documentary obligations (IVDR Art 5.5), the performance and safety specifications of ANNEX I, and development and manufacture under an ISO 15189-equivalent quality system apply. LDTs serve specific clinical needs, often for low volume niche applications, or correspond to the translational phase of new tests and treatments, often extremely relevant for patient care. As some commercial tests may disappear with the IVDR roll-out, many will require urgent LDT replacement. The workload will also depend on which modifications to commercial tests turns them into an LDT, and on how national legislators and competent authorities (CA) will handle new competences and responsibilities. We discuss appropriate interpretation of ISO 15189 to cover IVDR requirements. Selected cases illustrate LDT implementation covering medical needs with commensurate management of risk emanating from intended use and/or design of devices. Unintended collateral damage of the IVDR comprises loss of non-profitable niche applications, increases of costs and wasted resources, and migration of innovative research to more cost-efficient environments. Taking into account local specifics, the legislative framework should reduce the burden on and associated opportunity costs for the health care system, by making diligent use of existing frameworks.

mHealth Systems Need a Privacy-by-Design Approach: Commentary on "Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review".

Brauneck and colleagues have combined technical and legal perspectives in their timely and valuable paper "Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review." Researchers who design mobile health (mHealth) systems must adopt the same privacy-by-design approach that privacy regulations (eg, General Data Protection Regulation) do. In order to do this successfully, we will have to overcome implementation challenges in privacy-enhancing technologies such as differential privacy. We will also have to pay close attention to emerging technologies such as private synthetic data generation.

Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review.

BACKGROUND: The collection, storage, and analysis of large data sets are relevant in many sectors. Especially in the medical field, the processing of patient data promises great progress in personalized health care. However, it is strictly regulated, such as by the General Data Protection Regulation (GDPR). These regulations mandate strict data security and data protection and, thus, create major challenges for collecting and using large data sets. Technologies such as federated learning (FL), especially paired with differential privacy (DP) and secure multiparty computation (SMPC), aim to solve these challenges. OBJECTIVE: This scoping review aimed to summarize the current discussion on the legal questions and concerns related to FL systems in medical research. We were particularly interested in whether and to what extent FL applications and training processes are compliant with the GDPR data protection law and whether the use of the aforementioned privacy-enhancing technologies (DP and SMPC) affects this legal compliance. We placed special emphasis on the consequences for medical research and development. METHODS: We performed a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). We reviewed articles on Beck-Online, SSRN, ScienceDirect, arXiv, and Google Scholar published in German or English between 2016 and 2022. We examined 4 questions: whether local and global models are "personal data" as per the GDPR; what the "roles" as defined by the GDPR of various parties in FL are; who controls the data at various stages of the training process; and how, if at all, the use of privacy-enhancing technologies affects these findings. RESULTS: We identified and summarized the findings of 56 relevant publications on FL. Local and likely also global models constitute personal data according to the GDPR. FL strengthens data protection but is still vulnerable to a number of attacks and the possibility of data leakage. These concerns can be successfully addressed through the privacy-enhancing technologies SMPC and DP. CONCLUSIONS: Combining FL with SMPC and DP is necessary to fulfill the legal data protection requirements (GDPR) in medical research dealing with personal data. Even though some technical and legal challenges remain, for example, the possibility of successful attacks on the system, combining FL with SMPC and DP creates enough security to satisfy the legal requirements of the GDPR. This combination thereby provides an attractive technical solution for health institutions willing to collaborate without exposing their data to risk. From a legal perspective, the combination provides enough built-in security measures to satisfy data protection requirements, and from a technical perspective, the combination provides secure systems with comparable performance with centralized machine learning applications.

Challenges and opportunities of sharing animal health data for research and disease management: a case study of bovine tuberculosis.

The sharing of animal disease data should be encouraged. The analysis of such data will broaden our knowledge of animal diseases and potentially provide insights into their management. However, the need to conform to data protection rules in the sharing of such data for analysis purposes often poses practical difficulties. This paper sets out the challenges and the methods used for the sharing of animal health data in England, Scotland and Wales - Great Britain - using bovine tuberculosis (bTB) data as a case study. The data sharing described is undertaken by the Animal and Plant Health Agency on behalf of the Department for Environment, Food and Rural Affairs and the Welsh and Scottish Governments. It should be noted that animal health data are held at the level of Great Britain (rather than the United Kingdom - which includes Northern Ireland), as Northern Ireland's Department of Agriculture, Environment and Rural Affairs has its own separate data systems. Bovine tuberculosis is the most significant and costly animal health problem facing cattle farmers in England and Wales. It can be devastating for farmers and farming communities and the control costs for taxpayers in Great Britain are over £150 million a year. The authors describe two methods of data sharing - first, where data are requested by, and delivered to, an academic institution for epidemiological or scientific analysis, and second, where data are proactively published in an accessible and meaningful way. They provide details of an example of the second method, namely, the free-to-access website â€Ëœinformation bovine TB' (https://ibtb.co.uk), which publishes bTB data for the benefit of the farming community and veterinary health professionals.

L'échange et le partage de données sur les maladies animales sont des pratiques à encourager. En effet, l'analyse de ces données permet d'étoffer les connaissances sur les maladies animales et peut aussi apporter un nouvel éclairage sur leur gestion. Néanmoins, la nécessité de se conformer aux règles sur la protection des données pose souvent des difficultés pratiques lors des échanges de ce type de données à des fins d'analyse. Les auteurs expliquent les difficultés rencontrées en matière d'échange de données de santé animale en Angleterre, en écosse et au Pays de Galles (Grande-Bretagne), ainsi que les méthodes utilisées, à partir de l'exemple concret des données relatives à la tuberculose bovine. L'échange et le partage de données sont réalisés par l'Agence britannique de santé animale et végétale, pour le compte du ministère britannique de l'Environnement, de l'Alimentation et des Affaires rurales et des gouvernements gallois et écossais. Il convient de préciser que les données de santé animale dont il s'agit sont celles conservées au niveau de la Grande-Bretagne seulement (et non du Royaume-Uni, qui inclut l'Irlande du Nord), étant donné que le ministère de l'Agriculture, de l'Environnement et des Affaires rurales de l'Irlande du Nord possède ses propres systèmes de données. La tuberculose bovine est le principal problème de santé animale auquel sont confrontés les éleveurs de bovins en Angleterre et au Pays de Galles, et le plus coûteux à traiter. La survenue de la tuberculose bovine est une catastrophe pour les éleveurs affectés et leur communauté. En outre, le coût annuel de son contrôle s'élève à plus de 150 millions de livres pour le contribuable britannique. Les auteurs décrivent deux méthodes d'échange et de partage de données : la première est celle où une institution de recherche demande et obtient l'accès à des données particulières afin de réaliser une étude épidémiologique ou scientifique ; la deuxième consiste à publier les données de manière proactive et constructive, en les rendant facilement accessibles. Un exemple concret de cette deuxième méthode est décrit en détail : il s'agit du site web d'information sur la tuberculose bovine (https://ibtb.co.uk), d'accès libre, qui diffuse des informations sur cette maladie à l'intention des éleveurs et des professionnels de la santé animale.

Convendría alentar la puesta en común de datos zoosanitarios, pues el análisis de estos datos nos ayudará a conocer más y mejor las enfermedades animales y, a la postre, puede darnos pistas sobre la mejor manera de afrontarlas. Ocurre a menudo, sin embargo, que el prescriptivo cumplimiento de las reglas de protección de datos plantee dificultades prácticas para poner estos datos en común con fines de análisis. Los autores, empleando como ejemplo un estudio sobre la tuberculosis bovina, describen esas dificultades y los métodos utilizados para compartir datos zoosanitarios en Inglaterra, Escocia y Gales (Gran Bretaña). En el ejemplo descrito, la Agencia de Sanidad Animal y Vegetal del Reino Unido fue la instancia que impulsó la puesta en común de los datos en nombre del Departamento de Medio Ambiente, Alimentación y Asuntos Rurales del Reino Unido y de los gobiernos galés y escocés. Conviene puntualizar que los datos zoosanitarios cubren el territorio de Gran Bretaña (y no de todo el Reino Unido, que incluye Irlanda del Norte), ya que el Departamento de Medio Ambiente, Alimentación y Asuntos Rurales norirlandés dispone de su propio sistema de datos independiente. La tuberculosis bovina es el problema zoosanitario más importante y oneroso al que hacen frente las explotaciones de vacuno en Inglaterra y Gales. Esta enfermedad no solo puede ser devastadora para los productores y profesionales del sector, sino que la lucha contra ella cuesta al contribuyente británico más de 150 millones de libras al año. Los autores describen dos métodos para compartir de datos: en el primero de ellos, un establecimiento universitario solicita y recibe los datos con fines de análisis científico o epidemiológico; en el segundo, una entidad toma la iniciativa de hacer públicos los datos de forma accesible y coherente. Los autores exponen en detalle un ejemplo del segundo procedimiento, a saber, el sitio web de información sobre la tuberculosis bovina (https://ibtb.co.uk) en libre acceso, en el cual se publican datos sobre la enfermedad dirigidos a los profesionales del sector pecuario y la sanidad animal.

Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs.

Dynamic consent management allows a data subject to dynamically govern her consent to access her data. Clearly, security and privacy guarantees are vital for the adoption of dynamic consent management systems. In particular, specific data protection guarantees can be required to comply with rules and laws (e.g., the General Data Protection Regulation (GDPR)). Since the primary instantiation of the dynamic consent management systems in the existing literature is towards developing sustainable e-healthcare services, in this paper, we study data protection issues in dynamic consent management systems, identifying crucial security and privacy properties and discussing severe limitations of systems described in the state of the art. We have presented the precise definitions of security and privacy properties that are essential to confirm the robustness of the dynamic consent management systems against diverse adversaries. Finally, under those precise formal definitions of security and privacy, we have proposed the implications of state-of-the-art tools and technologies such as differential privacy, blockchain technologies, zero-knowledge proofs, and cryptographic procedures that can be used to build dynamic consent management systems that are secure and private by design.

Enhancing Safety on Construction Sites: A UWB-Based Proximity Warning System Ensuring GDPR Compliance to Prevent Collision Hazards.

Construction is known as one of the most dangerous industries in terms of worker safety. Collisions due the excessive proximity of workers to moving construction vehicles are one of the leading causes of fatal and non-fatal accidents on construction sites internationally. Proximity warning systems (PWS) have been proposed in the literature as a solution to detect the risk for collision and to alert workers and equipment operators in time to prevent collisions. Although the role of sensing technologies for situational awareness has been recognised in previous studies, several factors still need to be considered. This paper describes the design of a prototype sensor-based PWS, aimed mainly at small and medium-sized construction companies, to collect real-time data directly from construction sites and to warn workers of a potential risk of collision accidents. It considers, in an integrated manner, factors such as cost of deployment, the actual nature of a construction site as an operating environment and data protection. A low-cost, ultra-wideband (UWB)-based proximity detection system has been developed that can operate with or without fixed anchors. In addition, the PWS is compliant with the General Data Protection Regulation (GDPR) of the European Union. A privacy-by-design approach has been adopted and privacy mechanisms have been used for data protection. Future work could evaluate the PWS in real operational conditions and incorporate additional factors for its further development, such as studies on the timely interpretation of data.

Record linkage of routine and cohort data of children in Portugal: challenges and opportunities when using record linkage as a tool for scientific research.

Linking records could serve as a useful tool for scientific research and as a facilitator for local policymaking. This article examines the challenges and opportunities for researchers to lawfully link routinely collected health and education data with cohort data of children when using it as a tool for scientific research in Portugal. Such linking can be lawfully conducted in Portugal if three requirements are met. First, data processing pursues a legitimate purpose, such as scientific research. Secondly, data linking complies with the legal obligations of research entities and researchers, acting as data controllers or processors, and it respects the rights of children as data subjects. Finally, data linking is based on the explicit written consent of those with parental responsibility for the child. So far, the implementation of the General Data Protection Regulation in Portugal has not facilitated record linkage. It is argued that further harmonised implementation of that Regulation across European Union and European Economic Area Member States, establishing a minimum shared denominator for record linkage in scientific research for the common good, including without explicit consent, is needed.

Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed.

Collaborative networks and data sharing initiatives are broadening the opportunities for the advancement of science. These initiatives offer greater transparency in science, with the opportunity for external research groups to reproduce, replicate, and extend research findings. Further, larger datasets offer the opportunity to identify homogeneous patterns within subgroups of individuals, where these patterns may be obscured by the heterogeneity of the neurobiological measure in smaller samples. However, data sharing and data pooling initiatives are not without their challenges, especially with new laws that may at first glance appear quite restrictive for open science initiatives. Interestingly, what is key to some of these new laws (i.e, the European Union's general data protection regulation) is that they provide greater control of data to those who "give" their data for research purposes. Thus, the most important element in data sharing is allowing the participants to make informed decisions about how they want their data to be used, and, within the law of the specific country, to follow the participants' wishes. This framework encompasses obtaining thorough informed consent and allowing the participant to determine the extent that they want their data shared, many of the ethical and legal obstacles are reduced to just monsters under the bed. In this manuscript we discuss the many options and obstacles for data sharing, from fully open, to federated learning, to fully closed. Importantly, we highlight the intersection of data sharing, privacy, and data ownership and highlight specific examples that we believe are informative to the neuroimaging community.

Data protection-compliant broad consent for secondary use of health care data and human biosamples for (bio)medical research: Towards a new German national standard.

BACKGROUND: The secondary use of deidentified but not anonymized patient data is a promising approach for enabling precision medicine and learning health care systems. In most national jurisdictions (e.g., in Europe), this type of secondary use requires patient consent. While various ethical, legal, and technical analyses have stressed the opportunities and challenges for different types of consent over the past decade, no country has yet established a national consent standard accepted by the relevant authorities. METHODS: A working group of the national Medical Informatics Initiative in Germany conducted a requirements analysis and developed a GDPR-compliant broad consent standard. The development included consensus procedures within the Medical Informatics Initiative, a documented consultation process with all relevant stakeholder groups and authorities, and the ultimate submission for approval via the national data protection authorities. RESULTS: This paper presents the broad consent text together with a guidance document on mandatory safeguards for broad consent implementation. The mandatory safeguards comprise i) independent review of individual research projects, ii) organizational measures to protect patients from involuntary disclosure of protected information, and iii) comprehensive information for patients and public transparency. This paper further describes the key issues discussed with the relevant authorities, especially the position on additional or alternative consent approaches such as dynamic consent. DISCUSSION: Both the resulting broad consent text and the national consensus process are relevant for similar activities internationally. A key challenge of aligning consent documents with the various stakeholders was explaining and justifying the decision to use broad consent and the decision against using alternative models such as dynamic consent. Public transparency for all secondary use projects and their results emerged as a key factor in this justification. While currently largely limited to academic medicine in Germany, the first steps for extending this broad consent approach to wider areas of application, including smaller institutions and medical practices, are currently under consideration.

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

BACKGROUND: The 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. OBJECTIVE: This 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. METHODS: Individual 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. RESULTS: Participants 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. CONCLUSIONS: The 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.

Controversies between regulations of research ethics and protection of personal data: informed consent at a cross-road.

This paper explores some key discrepancies between two sets of normative requirements applicable to the research use of personal data and human biological materials: (a) the data protection regime which follows the application of the European Union General Data Protection Regulation (GDPR), and (b) the Declaration of Helsinki, CIOMS guidelines and other research ethics regulations. One source of this controversy is that the GDPR requires consent to process personal data to be clear, concise, specific and granular, freely given and revocable and therefore has challenged the concept of 'broad consent', which has been widely applied in the context of biobanking. Another source of controversy is the interplay between regulations of research ethics and protection of personal data related to the secondary use of personal data and biological materials. In this case, the GDPR 'research condition' provides an alternative to re-consent for the use of previously collected personal data and biological materials. Although the mentioned controversies have been raised in the legal literature, they have not been explicitly addressed from the research ethics perspective. Should consent be regarded as a priority legal basis for personal data processing in health data research? Can broad consent still be a suitable legal ground for biobanking? What should be the role of research ethics provisions that differ from the GDPR standards, and what should be the role and function of research ethics committees in the changing environment of health data research? These are the ongoing controversies to be explored in the paper.

The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data.

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.

Exploring the prevalence and profile of epilepsy across Europe using a standard retrospective chart review: Challenges and opportunities.

OBJECTIVE: This study aimed to determine the prevalence of epilepsy in four European countries (Austria, Denmark, Ireland, and Romania) employing a standard methodology. The study was conducted under the auspices of ESBACE (European Study on the Burden and Care of Epilepsy). METHODS: All hospitals and general practitioners serving a region of at least 50 000 persons in each country were asked to identify patients living in the region who had a diagnosis of epilepsy or experienced a single unprovoked seizure. Medical records were accessed, where available, to complete a standardized case report form. Data were sought on seizure frequency, seizure type, investigations, etiology, comorbidities, and use of antiseizure medication. Cases were validated in each country, and the degree of certainty was graded as definite, probable, or suspect cases. RESULTS: From a total population of 237 757 in the four countries, 1988 (.8%) patients were identified as potential cases of epilepsy. Due to legal and ethical issues in the individual countries, medical records were available for only 1208 patients, and among these, 113 had insufficient clinical information. The remaining 1095 cases were classified as either definite (n = 706, 64.5%), probable (n = 191, 17.4%), suspect (n = 153, 14.0%), or not epilepsy (n = 45, 4.1%). SIGNIFICANCE: Although a precise prevalence estimate could not be generated from these data, the study found a high validity of epilepsy classification among evaluated cases (95.9%). More generally, this study highlights the significant challenges facing epidemiological research methodologies that are reliant on patient consent and retrospective chart review, largely due to the introduction of data protection legislation during the study period. Documentation of the epilepsy diagnosis was, in some cases, relatively low, indicating a need for improved guidelines for assessment, follow-up, and documentation. This study highlights the need to address the concerns and requirements of recruitment sites to engage in epidemiological research.

How to address data privacy concerns when using social media data in conservation science.

Social media data are being increasingly used in conservation science to study human-nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects' rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.

Cómo Abordar las Preocupaciones por Privacidad al Usar las Redes Sociales en las Ciencias de las Conservación Resumen Cada vez se usan más los datos de las redes sociales en las ciencias de la conservación para estudiar las interacciones humano-naturaleza. El contenido generado por usuarios (imágenes, videos, textos y audios) y los metadatos asociados a estos pueden usarse para evaluar dichas interacciones. Un gran número de redes sociales proporcionan acceso gratuito al contenido generado por usuarios en las redes sociales. Sin embargo, como con cualquier investigación que involucre personas, las investigaciones basadas en los datos obtenidos de la redes sociales requieren cumplir con los estándares más altos de privacidad de datos y protección de la información, incluso cuando éstos están disponibles públicamente. En caso de que se le dé un uso inapropiado a la información obtenida de las redes sociales, los riesgos para la privacidad del usuario y para su bienestar pueden ser sustanciales. Investigamos las bases legales para el uso de la información de redes sociales en conjunto con la garantía de derechos para los sujetos de la información por medio de un estudio de caso basado en la Regulación de la Protección de Datos Generales (GDPR) de la Unión Europea (EU). Los riesgos asociados con el uso de información de las redes sociales en la investigación incluyen la identificación errónea accidental o intencional, la cual tiene el potencial de ocasionar daño psicológico o físico a la persona identificada. Para recolectar, almacenar, proteger, compartir y administrar la información de las redes sociales de manera que se prevengan los riesgos potenciales para los usuarios involucrados, se deben minimizar los datos, volverlos anónimos y seguir un procedimiento estricto de manejo de datos. Las estrategias basadas en riesgos, como la evaluación del impacto de la privacidad de datos, pueden usarse para identificar y minimizar los riesgos de privacidad presentes para los usuarios de las redes, para demostrar responsabilidades y para cumplir con la legislación de protección de datos. Recomendamos a los científicos de la conservación que consideren con cuidado nuestras recomendaciones para el diseño de sus objetivos de investigación para así facilitar el uso responsable de la información de redes sociales en la investigación de las ciencias de la conservación, por ejemplo para las investigaciones sobre el mercado ilegal de fauna en línea y para la culturomia de la conservación.

Development of a Web GIS for small-scale detection and analysis of COVID-19 (SARS-CoV-2) cases based on volunteered geographic information for the city of Cologne, Germany, in July/August 2020.

BACKGROUND: Various applications have been developed worldwide to contain and to combat the coronavirus disease-19 (COVID-19) pandemic. In this context, spatial information is always of great significance. The aim of this study is to describe the development of a Web GIS based on open source products for the collection and analysis of COVID-19 cases and its feasibility in terms of technical implementation and data protection. METHODS: With the help of this Web GIS, data on this issue were collected voluntarily from the Cologne area. Using house perimeters as a data basis, it was possible to check, in conjunction with the Official Topographic Cartographic Information System object type catalog, whether buildings with certain functions, for example residential building with trade and services, have been visited more frequently by infected persons than other types of buildings. In this context, data protection and ethical and legal issues were considered. RESULTS: The results of this study show that the development of a Web GIS for the generation and evaluation of volunteered geographic information (VGI) with the help of open source software is possible. Furthermore, there are numerous data protection and ethical and legal aspects to consider, which not only affect VGI per se but also affect IT security. CONCLUSIONS: From a data protection perspective, more attention needs to be paid to the intervention and post-processing of data. In addition, official data must always be used as a reference for the actual spatial consideration of the number of infections. However, VGI provides added value at a small-scale level, so that valid information can also be reliably derived in the context of health issues. The creation of guidelines for the consideration of data protection, ethical aspects, and legal requirements in the context of VGI-based applications must also be considered. Trial registration The article does not report the results of a health care intervention for human participants.

Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis.

Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely upon bespoke data sharing contracts. The lengthy process and administration induced by these contracts increases the inefficiency of data sharing and may disincentivize important clinical treatment and medical research. This paper provides a synthesis between 2 novel advanced privacy-enhancing technologies-homomorphic encryption and secure multiparty computation (defined together as multiparty homomorphic encryption). These privacy-enhancing technologies provide a mathematical guarantee of privacy, with multiparty homomorphic encryption providing a performance advantage over separately using homomorphic encryption or secure multiparty computation. We argue multiparty homomorphic encryption fulfills legal requirements for medical data sharing under the European Union's General Data Protection Regulation which has set a global benchmark for data protection. Specifically, the data processed and shared using multiparty homomorphic encryption can be considered anonymized data. We explain how multiparty homomorphic encryption can reduce the reliance upon customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research while offering additional incentives for health care and research institutes to employ common data interoperability standards.

A Smart Contract-Based Dynamic Consent Management System for Personal Data Usage under GDPR.

A massive amount of sensitive personal data is being collected and used by scientists, businesses, and governments. This has led to unprecedented threats to privacy rights and the security of personal data. There are few solutions that empower individuals to provide systematic consent agreements on distinct personal information and control who can collect, access, and use their data for specific purposes and periods. Individuals should be able to delegate consent rights, access consent-related information, and withdraw their given consent at any time. We propose a smart-contract-based dynamic consent management system, backed by blockchain technology, targeting personal data usage under the general data protection regulation. Our user-centric dynamic consent management system allows users to control their personal data collection and consent to its usage throughout the data lifecycle. Transaction history and logs are recorded in a blockchain that provides trusted tamper-proof data provenance, accountability, and traceability. A prototype of our system was designed and implemented to demonstrate its feasibility. The acceptability and reliability of the system were assessed by experimental testing and validation processes. We also analyzed the security and privacy of the system and evaluated its performance.