ABSTRACT
One of the major regulatory factors for health informatics is data privacy protection. In the European Union, a shared set of laws has been implemented - the General Data Protection Regulation. While this set of rules aims at harmonizing the European data privacy protection standards, it fails in properly detailing the handling of anonymized data. This is a problem, as, for example many current research initiatives aim at reusing patient data collected within primary care, but lack a patient consent, hence, might rely on anonymized data as being the only alternative. Within this work, we detail different aspects why the concept of anonymity is wrongly handled within the GDPR and give suggestions how the laws could be adapted.
Subject(s)
Biomedical Research , Computer Security , Medical Informatics , European Union , Humans , PrivacyABSTRACT
BACKGROUND: The identity management is a central component in medical research. Patients are recruited from various sites, which requires an error tolerant record linkage method, to ensure that patients are registered only once. In large research projects or institutions, the identity management has to deal with several thousands or millions of patients. In environments with large numbers of patients the register process could lead to high runtimes caused by record linkage. The Central Biomaterial Bank of the Charité (ZeBanC) searched for an identity management solution, which can handle millions of patients in large research projects with an acceptable performance. The goal of this paper was to simulate the registration of several million patients using the E-PIX service at Charité - Universitätsmedizin Berlin. The E-PIX service was evaluated in terms of needed runtimes, memory requirements, and processor utilization. A total of at least 20 million patients had to be registered. The runtimes to register patients into databases with various sizes should be examined, and the maximum number of patients, which the E-PIX service could handle, should be determined. METHODS: Tools were set up or developed to measure the needed runtimes, the memory used and the processor usage to register patients into various sizes of databases. To generate runtimes close to reality, modified patient data based on transposed real patient data were used for the simulation. The transposed patient data were sent to E-PIX to measure the runtimes of the registration process. This measurement was repeated for various database sizes. RESULTS: E-PIX is suitable to manage multi-million patients within a dataset. With the given hardware, it was possible to register a total of more than 30 million patients. It was possible to register more than 16 thousand patients per day into this database. CONCLUSIONS: The E-PIX tool fulfills the requirements of the Charité to be used for large research projects. The use of E-PIX is intended for the research context in the Charité.
Subject(s)
Biomedical Research , Medical Record Linkage , Databases, Factual , Germany , Hospitals , HumansABSTRACT
INTRODUCTION: In the context of an increasing number of multi-centric studies providing data from different sites and sources the necessity for central data management (CDM) becomes undeniable. This is exacerbated by a multiplicity of featured data types, formats and interfaces. In relation to methodological medical research the definition of central data management needs to be broadened beyond the simple storage and archiving of research data. OBJECTIVES: This paper highlights typical requirements of CDM for cohort studies and registries and illustrates how orientation for CDM can be provided by addressing selected data management challenges. METHODS: Therefore in the first part of this paper a short review summarises technical, organisational and legal challenges for CDM in cohort studies and registries. A deduced set of typical requirements of CDM in epidemiological research follows. RESULTS: In the second part the MOSAIC project is introduced (a modular systematic approach to implement CDM). The modular nature of MOSAIC contributes to manage both technical and organisational challenges efficiently by providing practical tools. A short presentation of a first set of tools, aiming for selected CDM requirements in cohort studies and registries, comprises a template for comprehensive documentation of data protection measures, an interactive reference portal for gaining insights and sharing experiences, supplemented by modular software tools for generation and management of generic pseudonyms, for participant management and for sophisticated consent management. CONCLUSIONS: Altogether, work within MOSAIC addresses existing challenges in epidemiological research in the context of CDM and facilitates the standardized collection of data with pre-programmed modules and provided document templates. The necessary effort for in-house programming is reduced, which accelerates the start of data collection.
Subject(s)
Epidemiologic Studies , Information Management/organization & administration , Computer Security , Medical InformaticsABSTRACT
The government had a plan to set up a new medical information law last October, which allows hospitals to share medical records of patients with given consent. The aim of this act is to manage and protect medical information effectively. However, civic groups and medical organizations strongly claim that there is a high possibility of leakage of individuals' private medical information that can raise conflicts of interest under the medical information act. Computerization of personal medical information is essential for the business efficiency, however, it may cause a serious damage to the society as well as to individuals should the information be used without the individuals' consent. In the age of knowledge and information, the improved medical service and its effectiveness via informatization is an unavoidable choice, however, it is also hoped that the issues of human rights be thoroughly considered in the process of medical informatization to prevent a potential aftermath to the people and the society.