FAIR compliant database development for human microbiome data samples.

Introduction: Sharing microbiome data among researchers fosters new innovations and reduces cost for research. Practically, this means that the (meta)data will have to be standardized, transparent and readily available for researchers. The microbiome data and associated metadata will then be described with regards to composition and origin, in order to maximize the possibilities for application in various contexts of research. Here, we propose a set of tools and protocols to develop a real-time FAIR (Findable. Accessible, Interoperable and Reusable) compliant database for the handling and storage of human microbiome and host-associated data. Methods: The conflicts arising from privacy laws with respect to metadata, possible human genome sequences in the metagenome shotgun data and FAIR implementations are discussed. Alternate pathways for achieving compliance in such conflicts are analyzed. Sample traceable and sensitive microbiome data, such as DNA sequences or geolocalized metadata are identified, and the role of the GDPR (General Data Protection Regulation) data regulations are considered. For the construction of the database, procedures have been realized to make data FAIR compliant, while preserving privacy of the participants providing the data. Results and discussion: An open-source development platform, Supabase, was used to implement the microbiome database. Researchers can deploy this real-time database to access, upload, download and interact with human microbiome data in a FAIR complaint manner. In addition, a large language model (LLM) powered by ChatGPT is developed and deployed to enable knowledge dissemination and non-expert usage of the database.

[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.

Towards a GDPR-compliant cloud architecture with data privacy controlled through sticky policies.

Data privacy is one of the biggest challenges facing system architects at the system design stage. Especially when certain laws, such as the General Data Protection Regulation (GDPR), have to be complied with by cloud environments. In this article, we want to help cloud providers comply with the GDPR by proposing a GDPR-compliant cloud architecture. To do this, we use model-driven engineering techniques to design cloud architecture and analyze cloud interactions. In particular, we develop a complete framework, called MDCT, which includes a Unified Modeling Language profile that allows us to define specific cloud scenarios and profile validation to ensure that certain required properties are met. The validation process is implemented through the Object Constraint Language (OCL) rules, which allow us to describe the constraints in these models. To comply with many GDPR articles, the proposed cloud architecture considers data privacy and data tracking, enabling safe and secure data management and tracking in the context of the cloud. For this purpose, sticky policies associated with the data are incorporated to define permission for third parties to access the data and track instances of data access. As a result, a cloud architecture designed with MDCT contains a set of OCL rules to validate it as a GDPR-compliant cloud architecture. Our tool models key GDPR points such as user consent/withdrawal, the purpose of access, and data transparency and auditing, and considers data privacy and data tracking with the help of sticky policies.

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.

[Legal integration of artificial intelligence into internal medicine : Data protection, regulatory, reimbursement and liability questions]. / Rechtliche Einordnung von künstlicher Intelligenz in der Inneren Medizin : Von Datenschutz und Regulatorik, Erstattungs- und Haftungsfragen.

Artificial intelligence (AI) opens up new opportunities to improve medical care in internal medicine; however, legal uncertainties in the application of AI impede its integration into the daily practice of internal medicine. To clarify the situation this paper gives an overview of the legal aspects related to AI and shows which frameworks must be adhered to in order to exploit the benefits of AI without neglecting the rights and protection of patients. The paper first addresses data protection issues which arise when sensitive health data are processed by AI. This is followed by a discussion of the key regulatory requirements for the use of AI in internal medicine. As the establishment of AI in practice also depends on sufficient funding, legal issues of reimbursement are additionally examined. Finally, the specific features that need to be considered when using AI to avoid medical liability consequences are highlighted.

Enhancing Women's Health: An Assessment of Data Privacy and Security of Menopause FemTech Applications.

Menopausal women increasingly rely on FemTech apps to manage their symptoms, as mobile applications can provide a convenient and easily accessible health solution. However, this scoping review and content analysis of 14 menopause apps available on Google Play in the European Union found that most applications categorisation is not aligning with their features as well as lack adequate data privacy and security sufficiency. Thereby sensitive health data of menopausal women are put at risk, highlighting the need for collaborative efforts between developers and regulators to implement effective and achievable data protection practices to enhance menopausal women's data safely.

Digital Platform for Continuous Monitoring of Patients Using a Smartwatch: Longitudinal Prospective Cohort Study.

BACKGROUND: Since the COVID-19 pandemic, there has been a boost in the digital transformation of the human society, where wearable devices such as a smartwatch can already measure vital signs in a continuous and naturalistic way; however, the security and privacy of personal data is a challenge to expanding the use of these data by health professionals in clinical follow-up for decision-making. Similar to the European General Data Protection Regulation, in Brazil, the Lei Geral de Proteção de Dados established rules and guidelines for the processing of personal data, including those used for patient care, such as those captured by smartwatches. Thus, in any telemonitoring scenario, there is a need to comply with rules and regulations, making this issue a challenge to overcome. OBJECTIVE: This study aimed to build a digital solution model for capturing data from wearable devices and making them available in a safe and agile manner for clinical and research use, following current laws. METHODS: A functional model was built following the Brazilian Lei Geral de Proteção de Dados (2018), where data captured by smartwatches can be transmitted anonymously over the Internet of Things and be identified later within the hospital. A total of 80 volunteers were selected for a 24-week follow-up clinical trial divided into 2 groups, one group with a previous diagnosis of COVID-19 and a control group without a previous diagnosis of COVID-19, to measure the synchronization rate of the platform with the devices and the accuracy and precision of the smartwatch in out-of-hospital conditions to simulate remote monitoring at home. RESULTS: In a 35-week clinical trial, >11.2 million records were collected with no system downtime; 66% of continuous beats per minute were synchronized within 24 hours (79% within 2 days and 91% within a week). In the limit of agreement analysis, the mean differences in oxygen saturation, diastolic blood pressure, systolic blood pressure, and heart rate were -1.280% (SD 5.679%), -1.399 (SD 19.112) mm Hg, -1.536 (SD 24.244) mm Hg, and 0.566 (SD 3.114) beats per minute, respectively. Furthermore, there was no difference in the 2 study groups in terms of data analysis (neither using the smartwatch nor the gold-standard devices), but it is worth mentioning that all volunteers in the COVID-19 group were already cured of the infection and were highly functional in their daily work life. CONCLUSIONS: On the basis of the results obtained, considering the validation conditions of accuracy and precision and simulating an extrahospital use environment, the functional model built in this study is capable of capturing data from the smartwatch and anonymously providing it to health care services, where they can be treated according to the legislation and be used to support clinical decisions during remote monitoring.

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.

The significance of general data protection regulation in the compliant data contribution to the European Society of Thoracic Surgeons database.

The General Data Protection Regulation (GDPR), enacted in the European Union in 2018, has significantly transformed the landscape of personal data management and protection. This article provides an overview of GDPR's impact, focusing on its applicability, fundamental principles and influence on data management practices, particularly within the European Society of Thoracic Surgeons (ESTS) database. GDPR's reach extends to all entities collecting and processing personal data of European Union residents, regardless of their location. It encompasses various data types, emphasizing meticulous handling and protection of identifiable information. Special categories of data, such as health and sensitive attributes, require even more stringent protection. The regulation sets legal, fair and transparent data processing principles, emphasizing accuracy, purpose limitation and data minimization. It also stresses accountability, leading to the appointment of Data Protection Officers and significant penalties for non-compliance. The ESTS database, designed to enhance thoracic surgical research and care, collects data on European procedures. It follows GDPR principles by pseudonymizing data, ensuring secure data transmission and providing clear instructions for data submission. The database contributes to research, policymaking and practice improvement in thoracic surgery by offering a comprehensive dataset for analysis. Here, we aim to shed light on the complexities of GDPR implementation and emphasize the need for comprehensive data management strategies to ensure compliance and enhance privacy protection with the contribution to the ESTS database. GDPR compliance comes with challenges, including potential human dignity and privacy rights violations. Data breaches can result in unauthorized disclosures, and non-compliance can lead to substantial fines and reputational damage. The implementation of GDPR encourages organizations to prioritize ethical data practices, security measures and transparent data handling. In conclusion, GDPR has revolutionized personal data protection by emphasizing accountability, transparency and individual rights. It has impacted organizations globally, promoting responsible data management practices. Adhering to GDPR ensures privacy protection, trust-building and overall enhancement of data management in today's data-driven environment.

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.

[The limits of internal medicine]. / Die Grenzen der Inneren Medizin.

"The limits of internal medicine" was the congress motto of the 128th Congress of the German Society of Internal Medicine in Wiesbaden in 2022. In his presidential address Prof. Lerch focused on four aspects of this motto: physician-assisted suicide, lessons from the corona pandemic, deficits in the digitalization of the German healthcare system and the German Sonderweg in applying EU regulations for patient data protection. Using data from Canada, Switzerland and the Netherlands, where different forms of physician-assisted suicide are practiced, Prof. Lerch appealed to internists, specifically in family practices, to confront this issue in view of a German Supreme Court ruling. With respect to the development of the corona pandemic he discussed the root causes of the opposition to vaccination in parts of society as well as the question why non-clinically active and only few clinical disciplines have shaped the discussion about corona protection measures in Germany. Another focus of his speech was the insufficient digital maturity of the German healthcare system, which clearly lags behind other countries with respect to digital transformation. Physicians need to become more involved in the digital transformation in order to reorganize the healthcare system for the benefit of the patients. The German Sonderweg in the application of the General Data Protection Regulation (GDPR) requires a new legal framework to enable a pragmatic and progressive use of patient data for medical research and patient safety.

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.

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.

Opportunities and Obstacles to the Development of Health Data Warehouses in Hospitals in France: The Recent Experience of Comprehensive Cancer Centers.

Big Data and Artificial Intelligence can profoundly transform medical practices, particularly in oncology. Comprehensive Cancer Centers have a major role to play in this revolution. With the purpose of advancing our knowledge and accelerating cancer research, it is urgent to make this pool of data usable through the development of robust and effective data warehouses. Through the recent experience of Comprehensive Cancer Centers in France, this article shows that, while the use of hospital data warehouses can be a source of progress by taking into account multisource, multidomain and multiscale data for the benefit of knowledge and patients, it nevertheless raises technical, organizational and legal issues that still need to be addressed. The objectives of this article are threefold: 1. to provide insight on public health stakes of development in Comprehensive Cancer Centers to manage cancer patients comprehensively; 2. to set out a challenge of structuring the data from within them; 3. to outline the legal issues of implementation to carry out real-world evidence studies. To meet objective 1, this article firstly proposed a discussion on the relevance of an integrated approach to manage cancer and the formidable tool that data warehouses represent to achieve this. To address objective 2, we carried out a literature review to screen the articles published in PubMed and Google Scholar through the end of 2022 on the use of data warehouses in French Comprehensive Cancer Centers. Seven publications dealing specifically with the issue of data structuring were selected. To achieve objective 3, we presented and commented on the main aspects of French and European legislation and regulations in the field of health data, hospital data warehouses and real-world evidence.

Patterns of utilization and clinical adoption of 0.35 Tesla MR-guided radiation therapy in the United States - Understanding the transition to adaptive, ultra-hypofractionated treatments.

Purpose/Objective: Magnetic resonance-guided radiation therapy (MRgRT) utilization is rapidly expanding worldwide, driven by advanced capabilities including continuous intrafraction visualization, automatic triggered beam delivery, and on-table adaptive replanning (oART). Our objective was to describe patterns of 0.35Tesla(T)-MRgRT (MRIdian) utilization in the United States (US) among early adopters of this novel technology. Materials/Methods: Anonymized administrative data from all US MRIdian treatment systems were extracted for patients completing treatment from 2014 to 2020. Detailed treatment information was available for all MRIdian linear accelerator (linac) systems and some cobalt systems. Results: Seventeen systems at 16 centers delivered 5736 courses and 36,389 fractions (fraction details unavailable for 1223 cobalt courses), of which 21.1% were adapted. Ultra-hypofractionation (UHfx) (1-5 fractions) was used in 70.3% of all courses. At least one adaptive fraction was used for 38.5% of courses (average 1.7 adapted fractions/course), with higher oART use in UHfx dose schedules (47.7% of courses, average 1.9 adapted fractions per course). The most commonly treated organ sites were pancreas (20.7%), liver (16.5%), prostate (12.5%), breast (11.5%), and lung (9.4%). Temporal trends show a compounded annual growth rate (CAGR) of 59.6% in treatment courses delivered, with a dramatic increase in use of UHfx to 84.9% of courses in 2020 and similar increase in use of oART to 51.0% of courses. Conclusions: This is the first comprehensive study reporting patterns of utilization among early adopters of MRIdian in the US. Intrafraction MR image-guidance, advanced motion management, and increasing adoption of adaptive radiation therapy has led to a substantial transition to ultra-hypofractionated regimens. 0.35 T-MRgRT has been predominantly used to treat abdominal and pelvic tumors with increasing use of on-table adaptive replanning, which represents a paradigm shift in radiation therapy.

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.

Implementation of data protection laws in the European Union and in California is associated with a move of clinical trials to countries with fewer data protections.

The European Union implemented data privacy laws in mid-2018 and the state of California enacted a similar law several weeks later. These regulations affect medical data collection and analysis. It is unclear if they achieve this goal in the realm of clinical trials. Here we investigate the effect of these laws on clinical trials through analysis of clinical trials recorded on the US's ClinicalTrials.gov, the World Health Organization's International Clinical Trials Registry Platform and scientific papers describing clinical trials. Our findings show that the number of phase 1 and 2 trials in countries not adhering to these data privacy laws rose significantly after implementation of these laws. The largest rise occurred in countries which are less free, as indicated by the negative correlation (-0.48, p = 0.008) between the civil liberties freedom score of countries and the increase in the number of trials. This trend was not observed in countries adhering to data privacy laws nor in the paper publication record. The rise was larger (and statistically significant) among industry funded trials and interventional trials. Thus, the implementation of data privacy laws is associated a change in the location of clinical trials, which are currently executed more often in countries where people have fewer protections for their data.