A workflow-driven approach to integrate generic software modules in a Trusted Third Party

A Scalable Pseudonymization Tool for Rapid Deployment in Large Biomedical Research Networks: Development and Evaluation Study

Background

The SARS-CoV-2 pandemic has demonstrated once again that rapid collaborative research is essential for the future of biomedicine. Large research networks are needed to collect, share, and reuse data and biosamples to generate collaborative evidence. However, setting up such networks is often complex and time-consuming, as common tools and policies are needed to ensure interoperability and the required flows of data and samples, especially for handling personal data and the associated data protection issues. In biomedical research, pseudonymization detaches directly identifying details from biomedical data and biosamples and connects them using secure identifiers, the so-called pseudonyms. This protects privacy by design but allows the necessary linkage and reidentification.

Objective

Although pseudonymization is used in almost every biomedical study, there are currently no pseudonymization tools that can be rapidly deployed across many institutions. Moreover, using centralized services is often not possible, for example, when data are reused and consent for this type of data processing is lacking. We present the ORCHESTRA Pseudonymization Tool (OPT), developed under the umbrella of the ORCHESTRA consortium, which faced exactly these challenges when it came to rapidly establishing a large-scale research network in the context of the rapid pandemic response in Europe.

Methods

To overcome challenges caused by the heterogeneity of IT infrastructures across institutions, the OPT was developed based on programmable runtime environments available at practically every institution: office suites. The software is highly configurable and provides many features, from subject and biosample registration to record linkage and the printing of machine-readable codes for labeling biosample tubes. Special care has been taken to ensure that the algorithms implemented are efficient so that the OPT can be used to pseudonymize large data sets, which we demonstrate through a comprehensive evaluation.

Results

The OPT is available for Microsoft Office and LibreOffice, so it can be deployed on Windows, Linux, and MacOS. It provides multiuser support and is configurable to meet the needs of different types of research projects. Within the ORCHESTRA research network, the OPT has been successfully deployed at 13 institutions in 11 countries in Europe and beyond. As of June 2023, the software manages data about more than 30,000 subjects and 15,000 biosamples. Over 10,000 labels have been printed. The results of our experimental evaluation show that the OPT offers practical response times for all major functionalities, pseudonymizing 100,000 subjects in 10 seconds using Microsoft Excel and in 54 seconds using LibreOffice.

Conclusions

Innovative solutions are needed to make the process of establishing large research networks more efficient. The OPT, which leverages the runtime environment of common office suites, can be used to rapidly deploy pseudonymization and biosample management capabilities across research networks. The tool is highly configurable and available as open-source software.

Data-driven sudden cardiac arrest research in Europe: Experts' perspectives on ethical challenges and governance strategies

Background

Observational studies using large-scale databases and biobanks help improve prevention and treatment of sudden cardiac arrest (SCA) but the lack of guidance on data protection issues in this setting may harm patients' rights and the research enterprise itself. This qualitative study explored the ethical aspects of observational SCA research, as well as solutions.

Methods

European experts in SCA research, medical ethics and health law reflected on this topic through semi-structured interviews (N = 29) and a virtual roundtable conference (N = 18). The ESCAPE-NET project served as a discussion case. Findings were coded and thematically analysed.

Results

The first theme concerned the potential benefits and harms (at individual and group level) of observational data-based SCA studies and included the following sub-themes: societal value, scientific validity, data privacy, disclosure of genetic findings, stigma and discrimination, and medicalisation of sudden death. The second theme involved governance through 'privacy by design', 'privacy by policy' and associated regulation and oversight. Sub-themes were: de-identification of data, informed consent (broad and deferred), ethics review, and harmonisation.

Conclusions

Researchers and scientific societies should be aware that ethico-legal issues may arise during data-driven studies in SCA and other emergencies. These can be mitigated by combining technical data protection safeguards with appropriate informed consent policies and proportional ethics oversight. To ensure responsible conduct of data research in emergency medicine, we recommend the establishment of 'codes of conduct' which should be developed in interdisciplinary groups and together with patient representatives.

Data integration between clinical research and patient care: A framework for context-depending data sharing and in silico predictions

The transfer of new insights from basic or clinical research into clinical routine is usually a lengthy and time-consuming process. Conversely, there are still many barriers to directly provide and use routine data in the context of basic and clinical research. In particular, no coherent software solution is available that allows a convenient and immediate bidirectional transfer of data between concrete treatment contexts and research settings. Here, we present a generic framework that integrates health data (e.g., clinical, molecular) and computational analytics (e.g., model predictions, statistical evaluations, visualizations) into a clinical software solution which simultaneously supports both patient-specific healthcare decisions and research efforts, while also adhering to the requirements for data protection and data quality. Specifically, our work is based on a recently established generic data management concept, for which we designed and implemented a web-based software framework that integrates data analysis, visualization as well as computer simulation and model prediction with audit trail functionality and a regulation-compliant pseudonymization service. Within the front-end application, we established two tailored views: a clinical (i.e., treatment context) perspective focusing on patient-specific data visualization, analysis and outcome prediction and a research perspective focusing on the exploration of pseudonymized data. We illustrate the application of our generic framework by two use-cases from the field of haematology/oncology. Our implementation demonstrates the feasibility of an integrated generation and backward propagation of data analysis results and model predictions at an individual patient level into clinical decision-making processes while enabling seamless integration into a clinical information system or an electronic health record.

Changes in social behavioral developmental risks in preschool children after the first COVID-19 wave: a prospective longitudinal cohort study

The impact of the COVID-19 pandemic on social-emotional developmental risks (SE-DR) of preschool children is largely unknown. Therefore, the aim of this prospective longitudinal dynamic cohort study was to assess changes in preschoolers' SE-DR from before the pandemic to after the first COVID-19 wave. SE-DR were assessed annually with the instrument "Dortmund Developmental Screening for Preschools" (DESK). Longitudinal DESK data from 3- to 4-year-old children who participated both in survey wave (SW) three (DESK-SW3, 2019) and SW four (DESK-SW4, 2020) from August 1 to November 30 were used, respectively. Additionally, data from previous pre-pandemic SW were analyzed to contextualize the observed changes (SW1: 2017; SW2: 2018). A total of N = 786 children were included in the analysis. In the pre-pandemic DESK-SW3, the proportion of children with SE-DR was 18.2%, whereas in DESK-SW4 after the first COVID-19 wave, the proportion decreased to 12.4% (p = 0.001). Thus, the prevalence rate ratio (PRR) was 0.68. Compared to data from previous SW (SW1-SW2: PRR = 0.88; SW2-SW3: PRR = 0.82), this result represents a notable improvement. However, only short-term effects were described, and the study region had one of the highest preschool return rates in Germany. Further studies are needed to examine long-term effects of the pandemic on preschoolers' SE-DR.

The DZHK research platform: maximisation of scientific value by enabling access to health data and biological samples collected in cardiovascular clinical studies

The German Centre for Cardiovascular Research (DZHK) is one of the German Centres for Health Research and aims to conduct early and guideline-relevant studies to develop new therapies and diagnostics that impact the lives of people with cardiovascular disease. Therefore, DZHK members designed a collaboratively organised and integrated research platform connecting all sites and partners. The overarching objectives of the research platform are the standardisation of prospective data and biological sample collections among all studies and the development of a sustainable centrally standardised storage in compliance with general legal regulations and the FAIR principles. The main elements of the DZHK infrastructure are web-based and central units for data management, LIMS, IDMS, and transfer office, embedded in a framework consisting of the DZHK Use and Access Policy, and the Ethics and Data Protection Concept. This framework is characterised by a modular design allowing a high standardisation across all studies. For studies that require even tighter criteria additional quality levels are defined. In addition, the Public Open Data strategy is an important focus of DZHK. The DZHK operates as one legal entity holding all rights of data and biological sample usage, according to the DZHK Use and Access Policy. All DZHK studies collect a basic set of data and biosamples, accompanied by specific clinical and imaging data and biobanking. The DZHK infrastructure was constructed by scientists with the focus on the needs of scientists conducting clinical studies. Through this, the DZHK enables the interdisciplinary and multiple use of data and biological samples by scientists inside and outside the DZHK. So far, 27 DZHK studies recruited well over 11,200 participants suffering from major cardiovascular disorders such as myocardial infarction or heart failure. Currently, data and samples of five DZHK studies of the DZHK Heart Bank can be applied for.

Cohort Profile: evaluation of the targeted individual promotion in german preschools using the revised Dortmund Developmental Screening for Preschools DESK 3-6 R (project "GIF MV")

This dynamic cohort was established to evaluate the targeted individual promotion of children affected by developmental risks as part of the German federal state law for child day-care and preschools in Mecklenburg-Western Pomerania. The project has been conducted in preschools in regions with a low socio-economic profile since 2011. Since 2017, the revision of the standardized Dortmund Developmental Screening for Preschools (DESK 3-6 R) has been applied. Developmental risks of 3 to 6-year-old children in the domains of motor, linguistic, cognitive and social competencies are monitored. The cohort is followed up annually. In 2020, n = 7,678 children from n = 152 preschools participated. At the baseline (2017), n = 8,439 children participated. Due to the defined age range of this screening, 3,000 to 4,000 5-6-year-old children leave the cohort annually. Simultaneously, an approximately equal number of 3-year-old children enters the cohort per survey wave. N = 702 children participated in all 4 survey waves. On the basis of DESK 3-6 R scores available from survey waves 2017 to 2019 it is possible to compute expected values for the survey wave 2020 and to compare those with the measured values to evaluate the effects of the COVID-19 pandemic (i.e. parental home care due to restrictions related to COVID-19).

We Know What You Agreed To, Don't We?-Evaluating the Quality of Paper-Based Consents Forms and Their Digitalized Equivalent Using the Example of the Baltic Fracture Competence Centre 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.

[The German Network of University Medicine: technical and organizational approaches for research data platforms]

The Network University Medicine (NUM) consists of 36 university clinics in Germany. It was set up to coordinate COVID-19 university medicine research activities on a national level. This required, among other things, common infrastructures for the collection, storage, and use of medical research data. These infrastructures were not available in the required form when the NUM started in April 2020. Medical research data are extremely heterogeneous and reach far beyond "real world data" from patient care. There was no "one size fits all" solution, so NUM built five infrastructures for different types of data, different ways of obtaining data, and different data origination settings. To prevent the creation of new data silos, all five infrastructures operate based on FAIR principles (findable, accessible, interoperable, reusable). In addition, NUM is implementing an overarching governance framework to manage the evolution of these five infrastructures. The article describes the current state of development and possible perspectives with a strong focus on technical and organizational aspects.

A FHIR has been lit on gICS: facilitating the standardised exchange of informed consent in a large network of university medicine

BACKGROUND

The Federal Ministry of Education and Research of Germany (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 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 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 supports data protection-compliant data processing and provides the consent management solutions gICS.

METHODS

Based on a stakeholder dialogue a required set of FHIR-functionalities was identified and technically specified supported by official FHIR experts. Next, a "TTP-FHIR Gateway" for the HL7 FHIR-compliant exchange of consent information using gICS was implemented. A last step included external integration tests and the development of a pre-configured consent template for the BC for the NUM sites.

RESULTS

A FHIR-compliant gICS-release and a corresponding consent template for the BC were provided to all NUM sites in June 2021. All FHIR functionalities comply with the already-balloted FHIR consent profiles of the HL7 Working Group Consent Management. The consent template simplifies the technical BC rollout and the corresponding implementation of the TFCI interoperability concept at the NUM sites.

CONCLUSIONS

This article shows 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.

3LGM2IHE: Requirements for Data-Protection-Compliant Research Infrastructures-A Systematic Comparison of Theory and Practice-Oriented Implementation

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.

Secondary use of health care data and left-over biosamples within the 'Medical Informatics Initiative' (MII): a quasi-randomized controlled evaluation of patient perceptions and preferences regarding the consent process

Background

Data collected during routine health care and ensuing analytical results bear the potential to provide valuable information to improve the overall health care of patients. However, little is known about how patients prefer to be informed about the possible usage of their routine data and/or biosamples for research purposes before reaching a consent decision. Specifically, we investigated the setting, the timing and the responsible staff for the information and consent process.

Methods

We performed a quasi-randomized controlled trial and compared the method by which patients were informed either in the patient admission area following patient admission by the same staff member (Group A) or in a separate room by another staff member (Group B). The consent decision was hypothetical in nature. Additionally, we evaluated if there was the need for additional time after the information session and before taking the consent decision. Data were collected during a structured interview based on questionnaires where participants reflected on the information and consent process they went through.

Results

Questionnaire data were obtained from 157 participants in Group A and 106 participants in Group B. Overall, participants in both groups were satisfied with their experienced process and with the way information was provided. They reported that their (hypothetical) consent decision was freely made. Approximately half of the interested participants in Group B did not show up in the separate room, while all interested participants in Group A could be informed about the secondary use of their routine data and left-over samples. No participants, except for one in Group B, wanted to take extra time for their consent decision. The hypothetical consent rate for both routine data and left-over samples was very high in both groups.

Conclusions

The willingness to support medical research by allowing the use of routine data and left-over samples seems to be widespread among patients. Information concerning this secondary data use may be given by trained administrative staff immediately following patient admission. Patients mainly prefer making a consent decision directly after information is provided and discussed. Furthermore, less patients are informed when the process is organized in a separate room.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01922-6.

Sovereign Digital Consent through Privacy Impact Quantification and Dynamic Consent

Digitization is becoming more and more important in the medical sector. Through electronic health records and the growing amount of digital data of patients available, big data research finds an increasing amount of use cases. The rising amount of data and the imposing privacy risks can be overwhelming for patients, so they can have the feeling of being out of control of their data. Several previous studies on digital consent have tried to solve this problem and empower the patient. However, there are no complete solution for the arising questions yet. This paper presents the concept of Sovereign Digital Consent by the combination of a consent privacy impact quantification and a technology for proactive sovereign consent. The privacy impact quantification supports the patient to comprehend the potential risk when sharing the data and considers the personal preferences regarding acceptance for a research project. The proactive dynamic consent implementation provides an implementation for fine granular digital consent, using medical data categorization terminology. This gives patients the ability to control their consent decisions dynamically and is research friendly through the automatic enforcement of the patients’ consent decision. Both technologies are evaluated and implemented in a prototypical application. With the combination of those technologies, a promising step towards patient empowerment through Sovereign Digital Consent can be made.

MAGICPL: A Generic Process Description Language for Distributed Pseudonymization Scenarios

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.

Telemedical care and quality of life in patients with schizophrenia and bipolar disorder: results of a randomized controlled trial

BACKGROUND

Schizophrenia and bipolar disorder are serious psychiatric disorders with a high disease burden, a high number of years of life lived with disability and a high risk for relapses and re-hospitalizations. Besides, both diseases are often accompanied with a reduced quality of life (QoL). A low level of quality of life is one predictor for relapses. This study examines whether a telemedical care program can improve QoL.

METHODS

Post stationary telemedical care of patients with severe psychiatric disorders" (Tecla) is a prospective controlled randomized intervention trial to implement and evaluate a telemedical care concept for patients with schizophrenia and bipolar disorder. Participants were randomized to an intervention or a control group. The intervention group received telemedical care including regular, individualized telephone calls and SMS-messages. QoL was measured with the German version of the WHOQOL-BREF. Effects of telemedicine on QoL after 6 months and treatment*time interactions were calculated using linear regressions (GLM and linear mixed models).

RESULTS

One hundred eighteen participants were recruited, thereof 57.6% men (n = 68). Participants were on average 43 years old (SD 13). The treatment*time interaction was not significant. Hence, treatment had no significant effect either. Instead, gender is an influencing factor. Further analysis showed that social support, the GAF-level and QoL-values at baselines were significant determinants for the improvement of QoL.

CONCLUSION

The telemedicine care concept Tecla was not significant for QoL in patients with severe psychiatric disorders. More important for the QoL is the general social support and the level of global functioning of the patients.

TRIAL REGISTRATION

German Clinical Trials Register, DRKS00008548, registered 21 May 2015 - retrospectively registered, https://www.drks.de/drks_web/setLocale_EN.do.

Designing and piloting a generic research architecture and workflows to unlock German primary care data for secondary use

Background

Medical data from family doctors are of great importance to health care researchers but seem to be locked in German practices and, thus, are underused in research. The RADAR project (Routine Anonymized Data for Advanced Health Services Research) aims at designing, implementing and piloting a generic research architecture, technical software solutions as well as procedures and workflows to unlock data from family doctor’s practices. A long-term medical data repository for research taking legal requirements into account is established. Thereby, RADAR helps closing the gap between the European countries and to contribute data from primary care in Germany.

Methods

The RADAR project comprises three phases: (1) analysis phase, (2) design phase, and (3) pilot. First, interdisciplinary workshops were held to list prerequisites and requirements. Second, an architecture diagram with building blocks and functions, and an ordered list of process steps (workflow) for data capture and storage were designed. Third, technical components and workflows were piloted. The pilot was extended by a data integration workflow using patient-reported outcomes (paper-based questionnaires).

Results

The analysis phase resulted in listing 17 essential prerequisites and guiding requirements for data management compliant with the General Data Protection Regulation (GDPR). Based on this list existing approaches to fulfil the RADAR tasks were evaluated—for example, re-using BDT interface for data exchange and Trusted Third Party-approach for consent management and record linkage. Consented data sets of 100 patients were successfully exported, separated into person-identifying and medical data, pseudonymised and saved. Record linkage and data integration workflows for patient-reported outcomes in the RADAR research database were successfully piloted for 63 responders.

Conclusion

The RADAR project successfully developed a generic architecture together with a technical framework of tools, interfaces, and workflows for a complete infrastructure for practicable and secure processing of patient data from family doctors. All technical components and workflows can be reused for further research projects. Additionally, a Trusted Third Party-approach can be used as core element to implement data privacy protection in such heterogeneous family doctor’s settings. Optimisations identified comprise a fully-electronic consent recording using tablet computers, which is part of the project’s extension phase.

Key components and IT assistance of participant management in clinical research: a scoping review

Objectives

Managing participants and their data are fundamental for the success of a clinical trial. Our review identifies and describes processes that deal with management of trial participants and highlights information technology (IT) assistance for clinical research in the context of participant management.

Methods

A scoping literature review design, based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement, was used to identify literature on trial participant-related proceedings, work procedures, or workflows, and assisting electronic systems.

Results

The literature search identified 1329 articles of which 111 were included for analysis. Participant-related procedures were categorized into 4 major trial processes: recruitment, obtaining informed consent, managing identities, and managing administrative data. Our results demonstrated that management of trial participants is considered in nearly every step of clinical trials, and that IT was successfully introduced to all participant-related areas of a clinical trial to facilitate processes.

Discussion

There is no precise definition of participant management, so a broad search strategy was necessary, resulting in a high number of articles that had to be excluded. Nevertheless, this review provides a comprehensive overview of participant management-related components, which was lacking so far. The review contributes to a better understanding of how computer-assisted management of participants in clinical trials is possible.

The generic Informed Consent Service gICS®: implementation and benefits of a modular consent software tool to master the challenge of electronic consent management in research

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.

MAGIC: once upon a time in consent management-a FHIR® tale

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.

Connecting healthcare and clinical research: Workflow optimizations through seamless integration of EHR, pseudonymization services and EDC systems

OBJECTIVE

In the last years, several projects promote the secondary use of routine healthcare data based on electronic health record (EHR) data. In multicenter studies, dedicated pseudonymization services are applied for unified pseudonym handling. Healthcare, clinical research and pseudonymization systems are generally disconnected. Hence, the aim of this research work is to integrate these applications and to evaluate the workflow of clinical research.

METHODS

We analyzed and identified technical solutions for legislation compliant automatic pseudonym generation and for the integration into EHR as well as electronic data capture (EDC) systems. The Mainzelliste was used as pseudonymization service, which is available as open source solution and compliant with the data privacy concept in Germany. Subject of the integration was the local EHR and an in-house developed EDC system. A time and motion study was conducted to evaluate the effects on the workflow.

RESULTS

Integration of EHR, pseudonymization service and EDC systems is technically feasible and leads to a less fragmented usage of all applications. Generated pseudonyms are obtained from the service hosted at a trusted third party and can now be used in the EDC as well as in the EHR system for direct access and re-identification. The evaluation of 90 registration iterations shows that the time for documentation has been significantly reduced in average by 39.6 s (56.3%) from 71 ± 8 s to 31 ± 5 s per registered study patient.

CONCLUSIONS

By incorporating EHR, EDC and pseudonymization systems, it is now feasible to support multicenter studies and registers out of an integrated system landscape within a hospital. Optimizing the workflow of patient registration for clinical research allows reduction of double data entry and transcription errors as well as a seamless transition from clinical routine to research data collection.

Data Integration for Future Medicine (DIFUTURE)

INTRODUCTION

This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Future medicine will be predictive, preventive, personalized, participatory and digital. Data and knowledge at comprehensive depth and breadth need to be available for research and at the point of care as a basis for targeted diagnosis and therapy. Data integration and data sharing will be essential to achieve these goals. For this purpose, the consortium Data Integration for Future Medicine (DIFUTURE) will establish Data Integration Centers (DICs) at university medical centers.

OBJECTIVES

The infrastructure envisioned by DIFUTURE will provide researchers with cross-site access to data and support physicians by innovative views on integrated data as well as by decision support components for personalized treatments. The aim of our use cases is to show that this accelerates innovation, improves health care processes and results in tangible benefits for our patients. To realize our vision, numerous challenges have to be addressed. The objective of this article is to describe our concepts and solutions on the technical and the organizational level with a specific focus on data integration and sharing.

GOVERNANCE AND POLICIES

Data sharing implies significant security and privacy challenges. Therefore, state-of-the-art data protection, modern IT security concepts and patient trust play a central role in our approach. We have established governance structures and policies safeguarding data use and sharing by technical and organizational measures providing highest levels of data protection. One of our central policies is that adequate methods of data sharing for each use case and project will be selected based on rigorous risk and threat analyses. Interdisciplinary groups have been installed in order to manage change.

ARCHITECTURAL FRAMEWORK AND METHODOLOGY

The DIFUTURE Data Integration Centers will implement a three-step approach to integrating, harmonizing and sharing structured, unstructured and omics data as well as images from clinical and research environments. First, data is imported and technically harmonized using common data and interface standards (including various IHE profiles, DICOM and HL7 FHIR). Second, data is preprocessed, transformed, harmonized and enriched within a staging and working environment. Third, data is imported into common analytics platforms and data models (including i2b2 and tranSMART) and made accessible in a form compliant with the interoperability requirements defined on the national level. Secure data access and sharing will be implemented with innovative combinations of privacy-enhancing technologies (safe data, safe settings, safe outputs) and methods of distributed computing.

USE CASES

From the perspective of health care and medical research, our approach is disease-oriented and use-case driven, i.e. following the needs of physicians and researchers and aiming at measurable benefits for our patients. We will work on early diagnosis, tailored therapies and therapy decision tools with focuses on neurology, oncology and further disease entities. Our early uses cases will serve as blueprints for the following ones, verifying that the infrastructure developed by DIFUTURE is able to support a variety of application scenarios.

DISCUSSION

Own previous work, the use of internationally successful open source systems and a state-of-the-art software architecture are cornerstones of our approach. In the conceptual phase of the initiative, we have already prototypically implemented and tested the most important components of our architecture.

Toolbox for Research, or how to facilitate a central data management in small-scale research projects

Background

In most research projects budget, staff and IT infrastructures are limiting resources. Especially for small-scale registries and cohort studies professional IT support and commercial electronic data capture systems are too expensive. Consequently, these projects use simple local approaches (e.g. Excel) for data capture instead of a central data management including web-based data capture and proper research databases. This leads to manual processes to merge, analyze and, if possible, pseudonymize research data of different study sites.

Results

To support multi-site data capture, storage and analyses in small-scall research projects, corresponding requirements were analyzed within the MOSAIC project. Based on the identified requirements, the Toolbox for Research was developed as a flexible software solution for various research scenarios. Additionally, the Toolbox facilitates data integration of research data as well as metadata by performing necessary procedures automatically. Also, Toolbox modules allow the integration of device data. Moreover, separation of personally identifiable information and medical data by using only pseudonyms for storing medical data ensures the compliance to data protection regulations. This pseudonymized data can then be exported in SPSS format in order to enable scientists to prepare reports and analyses.

Conclusions

The Toolbox for Research was successfully piloted in the German Burn Registry in 2016 facilitating the documentation of 4350 burn cases at 54 study sites. The Toolbox for Research can be downloaded free of charge from the project website and automatically installed due to the use of Docker technology.

MOVING: Motivation-Oriented interVention study for the elderly IN Greifswald: study protocol for a randomized controlled trial

BACKGROUND

Cardiovascular diseases (CVD) are the leading cause of mortality. In 2014, they were responsible for 38.9% of all causes of death in Germany. One major risk factor for CVD is a lack of physical activity (PA). A health-promoting lifestyle including regular PA and minimizing sitting time (ST) in daily life is a central preventive measure. Previous studies have shown that PA decreases in older age; 2.4-29% of the people aged over 60 years achieve the World Health Organization recommendations. This age group spends on average 9.4 h per day in sedentary activities. To increase PA and decrease ST, a low-threshold intervention, consisting of individualized feedback letters based on objectively measured data of PA and ST, was developed. The research question is: Do individual feedback letters, based on accelerometer data, have a positive effect on PA and ST?

METHODS/DESIGN

MOVING is a two-arm, randomized controlled trial. Inclusion criteria are age ≥ 65 years and the ability to be physically active. Exclusion criteria are the permanent use of a wheelchair and simultaneous participation in another study on PA. At baseline participants who give informed consent will receive general information and recommendations about the positive effects of regular PA and less ST. Participants of both groups will receive an accelerometer device, which records PA and ST over a period of seven consecutive days following by a randomization. Participants in the intervention group will receive automatically generated, individualized feedback letters by mail based on their PA and ST at baseline and at 3-month follow-up. Further follow-up examinations will be carried out at 6 and 12 months. The primary outcome is the increase of PA and the reduction of ST after 6 months in the intervention group compared to the control group.

DISCUSSION

The goal of the study is to examine the effects of a simple feedback intervention on PA and ST in elderly people. We aim to achieve an effect of 20% increase in moderate-to-vigorous physical activity (MVPA). The intervention may have the potential to decrease crucial cardiovascular risk factors and, therefore, contribute to prevention of CVD.

TRIAL REGISTRATION

German Clinical Trials Register, ID: DRKS00010410 . Registered on 17 May 2017.

Data privacy management and data quality monitoring in the German Centre for Cardiovascular Research's multicentre TranslatiOnal Registry for CardiomyopatHies (DZHK-TORCH)

Aims

The multicentric TranslatiOnal Registry for CardiomyopatHies (TORCH) of the German Centre for Cardiovascular Research aims to recruit 2300 patients with non‐ischemic cardiomyopthies.

Methods and results

The investigations were performed after standard operating procedures. The data are collected in standardized electronic case report forms provided by the data holding of the central data management of the German Centre for Cardiovascular Research using secuTrial (interActive Systems GmbH, Berlin, Germany). The personal‐identifying data and informed consent are collected, stored, and quality‐checked by the independent Trusted Third Party in Greifswald. The quality management of the medical data is performed by the data and quality centre Greifswald. In December 2014, the recruitment for TORCH has started. Currently, data and biomaterial from about 1397 patients and more than 74 500 biomaterial aliquots were collected. Regular study centre‐specific quality reports address completeness and plausibility of data and provide detailed information about current missing or implausible data entries to improve the data quality by using a query management in addition.

Conclusions

A regular quality control and reporting improve the data quality in TORCH and will support high‐quality data analysis and the translation of research results into routine care.

A generic solution for web-based management of pseudonymized data

BACKGROUND

Collaborative collection and sharing of data have become a core element of biomedical research. Typical applications are multi-site registries which collect sensitive person-related data prospectively, often together with biospecimens. To secure these sensitive data, national and international data protection laws and regulations demand the separation of identifying data from biomedical data and to introduce pseudonyms. Neither the formulation in laws and regulations nor existing pseudonymization concepts, however, are precise enough to directly provide an implementation guideline. We therefore describe core requirements as well as implementation options for registries and study databases with sensitive biomedical data.

METHODS

We first analyze existing concepts and compile a set of fundamental requirements for pseudonymized data management. Then we derive a system architecture that fulfills these requirements. Next, we provide a comprehensive overview and a comparison of different technical options for an implementation. Finally, we develop a generic software solution for managing pseudonymized data and show its feasibility by describing how we have used it to realize two research networks.

RESULTS

We have found that pseudonymization models are highly heterogeneous, already on a conceptual level. We have compiled a set of requirements from different pseudonymization schemes. We propose an architecture and present an overview of technical options. Based on a selection of technical elements, we suggest a generic solution. It supports the multi-site collection and management of biomedical data. Security measures are multi-tier pseudonymity and physical separation of data over independent backend servers. Integrated views are provided by a web-based user interface. Our approach has been successfully used to implement a national and an international rare disease network.

CONCLUSIONS

We were able to identify a set of core requirements out of several pseudonymization models. Considering various implementation options, we realized a generic solution which was implemented and deployed in research networks. Still, further conceptual work on pseudonymity is needed. Specifically, it remains unclear how exactly data is to be separated into distributed subsets. Moreover, a thorough risk and threat analysis is needed.

Tecla: a telephone- and text-message based telemedical concept for patients with severe mental health disorders--study protocol for a controlled, randomized, study

BACKGROUND

Severe mental disorders like psychotic disorders including schizophrenia and schizoaffective disorders have a 12-month-prevalence of 2.6, bipolar disorders of 1.5% in Germany. The relapse risk is high; so many patients need intensive monitoring and lifelong treatment. A high medication adherence is essential for a successful treatment. But in practice, medication adherence is low and decreases over time. Telemedical care concepts might improve treatment and bridge gaps between in- and outpatient treatment. A telemedical care concept based on regular telephone calls and short text messages was developed. The primary objective is to assess whether regular telephone calls and text messages can improve the medication adherence of patients. Secondary objectives are the reduction of rehospitalization rates, the improvement of quality of life and of the severity of symptoms.

METHODS/DESIGN

The Tecla study (Post stationary telemedical care of patients with severe psychiatric disorders) is a two-armed prospective randomized controlled trial. The participants in the intervention group receive in addition to usual care regular telephone calls every 2 weeks and weekly text messages on patient-individual topics during a 6 months period. Patients in the control group receive only regular care. Inclusion criteria are a physician-diagnosed bipolar disorder, schizoaffective disorder or schizophrenia and a signed informed consent. Exclusion criteria are planned inpatient treatments within the next 6 months and being non-reachable by phone. After 3 and 6 months both groups receive follow up assessments.

DISCUSSION

The primary objective of this study is the medication adherence that is measured with the Medication Adherence Report Scale, German version (MARS-D). The MARS-D is a self-report with five items. Adherent behaviour is mostly overestimated using self-reports. The strength of the MARS-D is to detect non-adherent behaviour. The original Medication Adherence Report Scale in English language (MARS-5) was developed to encourage the patient to answer truthfully to the questions that are asked in a non-threatening and non-judgmental way to minimize social desirability bias in admitting non-adherent behaviour.

TRIAL REGISTRATION

This study is registered at 2015\05\21 at the German Clinical Trials Register DRKS00008548.