[Monitoring of coercive measures and compulsory treatment in Germany]. / Monitoring von Zwangsmaßnahmen und Zwangsbehandlungen in Deutschland.

Epidemiological registers on the burden of disease and adverse events (deaths, serious side effects, etc.) play an important role in the management, evaluation, and improvement of healthcare treatment for the population. This also applies to coercive measures in the psychiatric healthcare system. Such registers only became feasible on a broad basis due to the availability of electronic medical records and steadily increasing computing capacities; however, in most German states, registers have not been implemented. Data protection problems must be taken into account in the collation of person-related data but can be solved by appropriate pseudonymization procedures taking the prerequisites of data parsimony into account. Extensive data are now available from the Baden-Wuerttemberg register for coercive measures, which has been in existence since 2015 and which enabled, for instance, evaluating the consequences of the changes to the law following the 2018 ruling of the Federal Constitutional Court on mechanical restraint and the consequences of the coronavirus pandemic. In the meantime, there are also state-wide data collections in some other German states; however, unlike in Baden-Wuerttemberg, these registers do not include measures under guardianship law. A nationwide register for coercive measures, compulsory treatment and involuntary detention has justifiably repeatedly been demanded for a long time. A major obstacle is the historically developed separation between the responsibility of the German states for the detention regulated by public law and the Federal State for the scope of application of the guardianship law.

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.