Zentralisierte Biobanken als Grundlage für die medizinische Forschung

Bernemann, Inga; Kersting, M.; Prokein, Jana; Hummel, Michael; Klopp, Norman; Illig, Thomas

doi:10.1007/s00103-015-2295-2

Cited by 16 publications

(14 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since its first release in 2013, Mainzelliste has been used by a constantly growing number of national medical research networks [6,7], centralized biobanks [8], research platforms [9], commercial data capture and analysis suites [10,11], registry software solutions [12,13] and patient organizations and related disease registries [14,15]. The software is under continuous development, incorporating community contributions from various research institutions [16].…”

Section: Mainzellistementioning

confidence: 99%

Optimization of the Mainzelliste software for fast privacy-preserving record linkage

et al. 2021

View full text Add to dashboard Cite

Background Data analysis for biomedical research often requires a record linkage step to identify records from multiple data sources referring to the same person. Due to the lack of unique personal identifiers across these sources, record linkage relies on the similarity of personal data such as first and last names or birth dates. However, the exchange of such identifying data with a third party, as is the case in record linkage, is generally subject to strict privacy requirements. This problem is addressed by privacy-preserving record linkage (PPRL) and pseudonymization services. Mainzelliste is an open-source record linkage and pseudonymization service used to carry out PPRL processes in real-world use cases. Methods We evaluate the linkage quality and performance of the linkage process using several real and near-real datasets with different properties w.r.t. size and error-rate of matching records. We conduct a comparison between (plaintext) record linkage and PPRL based on encoded records (Bloom filters). Furthermore, since the Mainzelliste software offers no blocking mechanism, we extend it by phonetic blocking as well as novel blocking schemes based on locality-sensitive hashing (LSH) to improve runtime for both standard and privacy-preserving record linkage. Results The Mainzelliste achieves high linkage quality for PPRL using field-level Bloom filters due to the use of an error-tolerant matching algorithm that can handle variances in names, in particular missing or transposed name compounds. However, due to the absence of blocking, the runtimes are unacceptable for real use cases with larger datasets. The newly implemented blocking approaches improve runtimes by orders of magnitude while retaining high linkage quality. Conclusion We conduct the first comprehensive evaluation of the record linkage facilities of the Mainzelliste software and extend it with blocking methods to improve its runtime. We observed a very high linkage quality for both plaintext as well as encoded data even in the presence of errors. The provided blocking methods provide order of magnitude improvements regarding runtime performance thus facilitating the use in research projects with large datasets and many participants.

show abstract

Section: Mainzellistementioning

confidence: 99%

Optimization of the Mainzelliste software for fast privacy-preserving record linkage

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In this respect, biomaterials stored in centralized biobanks need to be linked to rich clinical information of the patients' course of disease. Future biomedical insights can only be achieved if those biobanks are connected as large networks which are able to provide sufficient data even for very small disease subgroups [9,64]. Predictive models are typically trained in data-driven procedures.…”

Section: Data Sciencementioning

confidence: 99%

“…Biobanks have also brought up several new aspects, like patient consent and ethical needs, because of insufficient or missing national legal regulation [30]. On the technical side, aspects like secure databases, standardization, documentation or pseudonymization need to be implemented [9,65,75]. All these issues have to be addressed in an integrated manner together with the management and analysis of big data.…”

Section: Introductionmentioning

confidence: 99%

Big data and precision medicine: challenges and strategies with healthcare data

Kraus

Lausser

Kühn

et al. 2018

Int J Data Sci Anal

Self Cite

View full text Add to dashboard Cite

Recent snapshots of the European progress on big data in health care and precision medicine reveal diverse perceptions of experts and the public, leading to the impression that algorithmic issues have the largest share among the challenges all health systems are faced with. Yet, from a comparison of different countries it is evident that the adaption and integration of heterogeneous data sources have a major impact on the advancement of precision medicine. Legal regulations for implementation and operation of healthcare networking are actively discussed in the public and gradually implemented in several countries. Based on a unified documentation, they are a perfect precondition for integrating distributed healthcare data to a big data platform with a reliable fact representation. Now, basic and clinical scientists have to be motivated to share their work with these data platforms. In this work, we aim to provide an overview on the common issues in big healthcare data applications and address the challenges for the involved scientific, clinical and administrative partners. We propose a possible strategy for a comprehensive data integration by iterating data harmonization, semantic enrichment and data analysis processes.

show abstract

“…1 This development can also be observed in Germany where many centralized biobanks have been established in the past decade. 2,3 The growing number of centralized biobanks in Germany made further coordination and harmonization among them necessary. Accordingly, the German Federal Ministry of Research and Education (BMBF) started funding the German Biobank Node (GBN) as a central hub for German biobank activities in 2013.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the German Biobank Node as Coordinating Institution of the German Biobank Alliance: Engaging with Stakeholders via Survey Research

Klingler

Jagwitz-Biegnitz

Hartung

et al. 2020

Biopreservation and Biobanking

Self Cite

View full text Add to dashboard Cite

Background: The German Biobank Node (GBN) is the central hub for German biobank activities and coordinates the German Biobank Alliance (GBA) to which 11 biobank sites in Germany belong. GBN, in cooperation with designated members of GBA, has developed various services and products for the German biobank community. To ensure that services and products are well aligned with the needs and interests of relevant stakeholders, GBN actively engages with its diverse stakeholder groups through different methods. Important stakeholder groups are the members of GBA who are generally the first users of developed products and services. Methods and Materials: Members of GBA were surveyed anonymously through a web-based application. The survey was sent to all members registered with an internal communication platform. Participants were primarily asked about their experiences with GBN, developed products and services, their wishes for the future of GBN/GBA, and their attitudes toward intensified cooperation on the European level. Answers were analyzed using descriptive statistics and qualitative content analysis. Results: Overall 63 of 110 registered GBA members (response rate of 57%) finished the survey. Participants were overall satisfied with the work of GBN and developed products and services. They also pointed out room for improvement. Participants, for example, proposed to shorten the survey developed for biobanks to engage with their users. They also shared what additional support wishes they had, for example, uniform cost models or use and access policies for the GBA community. Discussion: The survey was helpful to get a good overview of the experiences and attitudes of GBA members before making services and products available to other actors in the German biobank community. GBN will use the feedback to improve its work and to guide future strategy development. Survey research has shown an adequate method to engage with this particular stakeholder group, but further research on choosing methods for stakeholder engagement might be helpful.

show abstract

Zentralisierte Biobanken als Grundlage für die medizinische Forschung

Cited by 16 publications

References 5 publications

Optimization of the Mainzelliste software for fast privacy-preserving record linkage

Optimization of the Mainzelliste software for fast privacy-preserving record linkage

Big data and precision medicine: challenges and strategies with healthcare data

Evaluating the German Biobank Node as Coordinating Institution of the German Biobank Alliance: Engaging with Stakeholders via Survey Research

Contact Info

Product

Resources

About