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From 1991-2014, all major burn centers of the German-speaking countries participated in a multicenter study in which essentially demographic data were collected. Individual patient data was located at the particular burn centers and only cumulated data were summarized annually for presentation. Retrospective statistical analysis of the entire data collection and identification of subgroups was not possible. In 2015 the German Burn Registry was established for prospective collection of individual patient data as a tool for quality management (QM) and for scientific analyses.A working group was formed to ensure the development and administration of the registry. From the official start of the German Burn Registry at the beginning of the year 2015 prospective data collection was realized with an individualized, web-based data collection software in a pseudonymized way. Selected data analysis was performed for the first 5 years of data collection. Severely burned adults and all hospitalized children with burn injuries were documented in the registry.The German Burn Registry was successfully established. 64 burn divisions have already been registered. 18,891 patients were documented over 5 years, of which 58% where children (16 years). Mean ABSI Score was 4 (children: 3, adults: 6) with a mortality rate of 3.8.0% (children: 0.2%, adults: 9.3%). Children were hospitalized for an average of 7 days, whereas adults were discharged after 18 days.A registry is mandatory for quality assurance in burn medicine, since realization of randomized studies is difficult due to the heterogeneity of burn injuries. The German Burn Registry already is one of the biggest burn registries in Europe. Several scientific projects, based on the registry database, are in working process or have already been published.

Objectives The TMF (Technology, Methods, and Infrastructure for Networked Medical Research) Data Protection Guide (TMF-DP) makes path-breaking recommendations on the subject of data protection in research projects. It includes comprehensive requirements for applications such as patient lists, pseudonymization services, and consent management services. Nevertheless, it lacks a structured, categorized list of requirements for simplified application in research projects and systematic evaluation. The 3LGM2IHE (“Three-layer Graphbased meta model – Integrating the Healthcare Enterprise [IHE] ” ) project is funded by the German Research Foundation (DFG). 3LGM2IHE aims to define modeling paradigms and implement modeling tools for planning health care information systems. In addition, one of the goals is to create and publish 3LGM2 information system architecture design patterns (short “design patterns”) for the community as design models in terms of a framework. A structured list of data protection-related requirements based on the TMF-DP is a precondition to integrate functions (3LGM2 Domain Layer) and building blocks (3LGM2 Logical Tool Layer) in 3LGM2 design patterns. Methods In order to structure the continuous text of the TMF-DP, requirement types were defined in a first step. In a second step, dependencies and delineations of the definitions were identified. In a third step, the requirements from the TMF-DP were systematically extracted. Based on the identified lists of requirements, a fourth step included the comparison of the identified requirements with exemplary open source tools as provided by the “Independent Trusted Third Party of the University Medicine Greifswald” (TTP tools). Results As a result, four lists of requirements were created, which contain requirements for the “patient list”, the “pseudonymization service”, and the “consent management”, as well as cross-component requirements from the TMF-DP chapter 6 in a structured form. Further to requirements (1), possible variants (2) of implementations (to fulfill a single requirement) and recommendations (3) were identified. A comparison of the requirements lists with the functional scopes of the open source tools E-PIX (record linkage), gPAS (pseudonym management), and gICS (consent management) has shown that these fulfill more than 80% of the requirements. Conclusions A structured set of data protection-related requirements facilitates a systematic evaluation of implementations with respect to the fulfillment of the TMF-DP guidelines. These re-usable lists provide a decision aid for the selection of suitable tools for new research projects. As a result, these lists form the basis for the development of data protection-related 3LGM2 design patterns as part of the 3LGM2IHE project.

Introduction The informed consent is the legal basis for research with human subjects. Therefore, the consent form (CF) as legally binding document must be valid, that is, be completely filled-in stating the person's decision clearly and signed by the respective person. However, especially paper-based CFs might have quality issues and the transformation into machine-readable information could add to low quality. This paper evaluates the quality and arising quality issues of paper-based CFs using the example of the Baltic Fracture Competence Centre (BFCC) fracture registry. It also evaluates the impact of quality assurance (QA) measures including giving site-specific feedback. Finally, it answers the question whether manual data entry of patients' decisions by clinical staff leads to a significant error rate in digitalized paper-based CFs. Methods Based on defined quality criteria, monthly QA including source data verification was conducted by two individual reviewers since the start of recruitment in December 2017. Basis for the analyses are the CFs collected from December 2017 until February 2019 (first recruitment period). Results After conducting QA internally, the sudden increase of quality issues in May 2018 led to site-specific feedback reports and follow-up training regarding the CFs' quality starting in June 2018. Specific criteria and descriptions on how to correct the CFs helped in increasing the quality in a timely matter. Most common issues were missing pages, decisions regarding optional modules, and signature(s). Since patients' datasets without valid CFs must be deleted, QA helped in retaining 65 datasets for research so that the final datapool consisted of 840 (99.29%) patients. Conclusion All quality issues could be assigned to one predefined criterion. Using the example of the BFCC fracture registry, CF-QA proved to significantly increase CF quality and help retain the number of available datasets for research. Consequently, the described quality indicators, criteria, and QA processes can be seen as the best practice approach.

Background The Federal Ministry of Education and Research (BMBF) funds a network of university medicines (NUM) to support COVID-19 and pandemic research at national level. The “COVID-19 Data Exchange Platform” (CODEX) as part of NUM establishes a harmonised infrastructure that supports decentral but standardised provision as well as federated combination and research use of COVID-19 datasets. The broad consent (BC) of the Medical Informatics Initiative (MII) is agreed by all German federal states and forms the legal base for such data processing. All 34 participating university hospitals (NUM sites) work upon a harmonised infrastructural as well as legal basis for their data protection-compliant collection and transfer of their research dataset to the central CODEX platform. Each NUM site ensures that the exchanged consent information conforms to the already-balloted HL7® FHIR® consent profiles and the interoperability concept of the MII Task Force “Consent Implementation” (TFCI). The Independent Trusted Third-Party (TTP) of the University Medicine Greifswald successfully supports data protection-compliant data processing in various research projects since 2014 and provides the consent management solutions gICS®, which supports fully digital and paper-based consent management. Results A “TTP-FHIR Gateway” for the HL7® FHIR®-compliant exchange of consent information using gICS® throughout NUM-CODEX was implemented and provided to all NUM sites in June 2021 as a separate software component. The gateway relies on the gICS® application logic. All FHIR® functionalities comply with the already-balloted FHIR® consent profiles of the HL7® Working Group Consent Management. A pre-configured consent template for the BC is provided to all NUM sites, thereby simplifying the technical BC rollout and the corresponding implementation of the TFCI interoperability concept at the NUM sites. Conclusions This article proves that a HL7® FHIR®-compliant and interoperable nationwide exchange of consent information could be built using of the consent management software gICS® and the provided TTP-FHIR Gateway. The initial functional scope of the solution covers the requirements identified in the NUM-CODEX setting. The semantic correctness of these functionalities was validated by project-partners from the Ludwig-Maximilian University in Munich. The production rollout of the solution package to all NUM sites has started successfully.

Objectives Pseudonymization is an important aspect of projects dealing with sensitive patient data. Most projects build their own specialized, hard-coded, solutions. However, these overlap in many aspects of their functionality. As any re-implementation binds resources, we would like to propose a solution that facilitates and encourages the reuse of existing components. Methods We analyzed already-established data protection concepts to gain an insight into their common features and the ways in which their components were linked together. We found that we could represent these pseudonymization processes with a simple descriptive language, which we have called MAGICPL, plus a relatively small set of components. We designed MAGICPL as an XML-based language, to make it human-readable and accessible to nonprogrammers. Additionally, a prototype implementation of the components was written in Java. MAGICPL makes it possible to reference the components using their class names, making it easy to extend or exchange the component set. Furthermore, there is a simple HTTP application programming interface (API) that runs the tasks and allows other systems to communicate with the pseudonymization process. Results MAGICPL has been used in at least three projects, including the re-implementation of the pseudonymization process of the German Cancer Consortium, clinical data flows in a large-scale translational research network (National Network Genomic Medicine), and for our own institute's pseudonymization service. Conclusions Putting our solution into productive use at both our own institute and at our partner sites facilitated a reduction in the time and effort required to build pseudonymization pipelines in medical research.

COVID-19 has challenged the healthcare systems worldwide. To quickly identify successful diagnostic and therapeutic approaches large data sharing approaches are inevitable. Though organizational clinical data are abundant, many of them are available only in isolated silos and largely inaccessible to external researchers. To overcome and tackle this challenge the university medicine network (comprising all 36 German university hospitals) has been founded in April 2020 to coordinate COVID-19 action plans, diagnostic and therapeutic strategies and collaborative research activities. 13 projects were initiated from which the CODEX project, aiming at the development of a Germany-wide Covid-19 Data Exchange Platform, is presented in this publication. We illustrate the conceptual design, the stepwise development and deployment, first results and the current status.

The academic research environment is characterized by self-developed, innovative, customized solutions, which are often free to use for third parties with open-source code and open licenses. On the other hand, they are maintained only to a very limited extent after the end of project funding. The ToolPool Gesundheitsforschung addresses the problem of finding ready to use solutions by building a registry of proven and supported tools, services, concepts and consulting offers. The goal is to provide an up-to-date selection of "relevant" solutions for a given domain that are immediately usable and that are actually used by third parties, rather than aiming at a complete list of all solutions which belong to that domain. Proof of relevance and usage must be provided, for example, by concrete application scenarios, experience reports by uninvolved third parties, references in publications or workshops held. Quality assurance is carried out for new entries by an agreed list of admission criteria, for existing entries at least once a year by a special task force. Currently, 79 solutions are represented, this number is to be significantly expanded by involving of new editors from current national funding initiatives in Germany.

Background Defining and protecting participants’ rights is the aim of several ethical codices and legal regulations. According to these regulations, the Informed Consent (IC) is an inevitable element of research with human subjects. In the era of “big data medicine”, aspects of IC become even more relevant since research becomes more complex rendering compliance with legal and ethical regulations increasingly difficult. Methods Based on literature research and practical experiences gathered by the Institute for Community Medicine (ICM), University Medicine Greifswald, requirements for digital consent management systems were identified. Results To address the requirements, the free-of-charge, open-source software “generic Informed Consent Service” (gICS®) was developed by ICM to provide a tool to facilitate and enhance usage of digital ICs for the international research community covering various scenarios. gICS facilitates IC management based on IC modularisation and supports various workflows within research, including (1) electronic depiction of paper-based consents and (2) fully electronic consents. Numerous projects applied gICS and documented over 336,000 ICs and 2400 withdrawals since 2014. Discussion Since the consent’s content is a prerequisite for securing participants’ rights, application of gICS is no guarantee for legal compliance. However, gICS supports fine-granular consents and accommodation of differentiated consent states, which can be directly exchanged between systems, allowing automated data processing. Conclusion gICS simplifies and supports sustained IC management as a major key to successfully conduct studies and build trust in research with human subjects. Therefore, interested researchers are invited to use gICS and provide feedback for further improvements.

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.

BackgroundThe Federal Ministry of Research and Education funded the Network of University Medicine for establishing an infrastructure for pandemic research. This includes the development of a COVID-19 Data Exchange Platform (CODEX) that provides standardised and harmonised data sets for COVID-19 research. Nearly all university hospitals in Germany are part of the project and transmit medical data from the local data integration centres to the CODEX platform. The medical data on a person that has been collected at several sites is to be made available on the CODEX platform in a merged form. To enable this, a federated trusted third party (fTTP) will be established, which will allow the pseudonymised merging of the medical data. The fTTP implements privacy preserving record linkage based on Bloom filters and assigns pseudonyms to enable re-pseudonymisation during data transfer to the CODEX platform.ResultsThe fTTP was implemented conceptually and technically. For this purpose, the processes that are necessary for data delivery were modelled. The resulting communication relationships were identified and corresponding interfaces were specified. These were developed according to the specifications in FHIR and validated with the help of external partners. Existing tools such as the identity management system E-PIX® were further developed accordingly so that sites can generate Bloom filters based on person identifying information. An extension for the comparison of Bloom filters was implemented for the federated trust third party. The correct implementation was shown in the form of a demonstrator and the connection of two data integration centres.ConclusionsThis article describes how the fTTP was modelled and implemented. In a first expansion stage, the fTTP was exemplarily connected through two sites and its functionality was demonstrated. Further expansion stages, which are already planned, have been technically specified and will be implemented in the future in order to also handle cases in which the privacy preserving record linkage achieves ambiguous results. The first expansion stage of the fTTP is available in the University Medicine network and will be connected by all participating sites in the ongoing test phase.

Background The consent management is an essential component for supporting the implementation of consents and withdrawals and thus, the realisation of patient’s rights. In MIRACUM, one of the four consortia of the Medical Informatics Initiative (MII), ten university hospitals intend to integrate the generic Informed Consent Service® (gICS) in their Data Integration Center (DIC). To provide a tool that supports the local workflows of the MIRACUM sites, the gICS should be improved. Methods We used three standardised questionnaires with 46 questions to elicit requirements from the ten sites. Each site answered the questions from the current and the desired future perspective. This made it possible to understand the individual processes at each site and it was possible to identify features and improvements that were generally necessary. Results The results of the survey were classified according to their impact on the gICS. Feature requests of new functionalities, improvements of already implemented functionalities and conceptual support for implementing processes were identified. This is the basis for an improved gICS release to support the ten sites’ individual consent management processes. Conclusions A release plan for the feature requests and improvements was coordinated with all sites. All sites have confirmed that the implementation of these features and enhancements will support their software-based consent management processes.

SummaryBackground: Epidemiological studies are based on a considerable amount of personal, medical and socio-economic data. To answer research questions with reliable results, epidemiological research projects face the challenge of providing high quality data. Consequently, gathered data has to be reviewed continuously during the data collection period.Objectives: This article describes the development of the mosaicQA-library for non-statistical experts consisting of a set of reusable R functions to provide support for a basic data quality assurance for a wide range of application scenarios in epidemiological research.Methods: To generate valid quality reports for various scenarios and data sets, a general and flexible development approach was needed. As a first step, a set of quality-related questions, targeting quality aspects on a more general level, was identified. The next step included the design of specific R-scripts to produce proper reports for metric and categorical data. For more flexibility, the third development step focussed on the generalization of the developed R-scripts, e.g. extracting characteristics and parameters. As a last step the generic characteristics of the developed R functionalities and generated reports have been evaluated using different metric and categorical datasets.Results: The developed mosaicQA-library generates basic data quality reports for multivariate input data. If needed, more detailed results for single-variable data, including definition of units, variables, descriptions, code lists and categories of qualified missings, can easily be produced.Conclusions: The mosaicQA-library enables researchers to generate reports for various kinds of metric and categorical data without the need for computational or scripting knowledge. At the moment, the library focusses on the data structure quality and supports the assessment of several quality indicators, including frequency, distribution and plausibility of research variables as well as the occurrence of missing and extreme values. To simplify the installation process, mosaicQA has been released as an official R-package.

Background The use of medical data for research purposes requires an informed consent of the patient that is compliant with the EU General Data Protection Regulation. In the context of multi-centre research initiatives and a multitude of clinical and epidemiological studies scalable and automatable measures for digital consent management are required. Modular form, structure, and contents render a patient’s consent reusable for varying project settings in order to effectively manage and minimise organisational and technical efforts. Results Within the DFG-funded project “MAGIC” (Grant Number HO 1937/5-1) the digital consent management service tool gICS was enhanced to comply with the recommendations published in the TMF data protection guideline for medical research. In addition, a structured exchange format for modular consent templates considering established standards and formats in the area of digital informed consent management was designed. Using the new FHIR standard and the HAPI FHIR library, the first version for an exchange format and necessary import-/export-functionalities were successfully implemented. Conclusions The proposed exchange format is a “work in progress”. It represents a starting point for current discussions concerning digital consent management. It also attempts to improve interoperability between different approaches within the wider IHE-/HL7-/FHIR community. Independent of the exchange format, providing the possibility to export, modify and import templates for consents and withdrawals to be reused in similar clinical and epidemiological studies is an essential precondition for the sustainable operation of digital consent management.

Summary 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.

Background Cohort studies and registries rely on massive amounts of personal medical data. Therefore, data protection and information security as well as ethical aspects gain in importance and need to be considered as early as possible during the establishment of a study. Resulting legal and ethical obligations require a precise implementation of appropriate technical and organisational measures for a Trusted Third Party. Methods This paper defines and organises a consistent workflow-management to realize a Trusted Third Party. In particular, it focusses the technical implementation of a Trusted Third Party Dispatcher to provide basic functionalities (including identity management, pseudonym administration and informed consent management) and measures required to meet study specific conditions of cohort studies and registries. Thereby several independent open source software modules developed and provided by the MOSAIC project are used. This technical concept offers the necessary flexibility and extensibility to address legal and ethical requirements of individual scenarios. Results The developed concept for a Trusted Third Party Dispatcher allows mapping single process steps as well as individual requirements and characteristics of particular studies to workflows, which in turn can be combined to model complex Trusted Third Party processes. The uniformity of this approach permits unrestricted re-combination of the available functionalities (depending on the applied software modules) for various research projects. Conclusion The proposed approach for the technical implementation of an independent Trusted Third Party reduces the effort for scenario specific implementations as well as for maintenance. The applicability and the efficacy of the concept for a workflow-driven Trusted Third Party could be confirmed during the establishment of several nationwide studies (e.g. German Centre for Cardiovascular Research and the National Cohort).