MOSAIC – A Modular Approach to Data Management in Epidemiological Studies

Bialke, Martin; Bahls, Thomas; Havemann, Christoph; Piegsa, Jens; Weitmann, Kerstin; Wegner, Tim; Hoffmann, Wolfgang

doi:10.3414/me14-01-0133

Cited by 33 publications

(44 citation statements)

References 13 publications

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“…We focused on the French and German projects, but other European countries also have started important projects in this domain. For instance, Switzerland has recently invested 1 million Swiss francs per hospital to promote the creation of health data centers [48], similar to the German DICs or the Clinical Data Centers in France. In 2018, the UK government published a national strategy to support AI development and health data sharing [53].…”

Section: Discussionmentioning

confidence: 99%

“…DIFUTURE has defined the role of a data protection specialist, a DIC member who reviews each request and analyzes the risks of data sharing. MIRACUM has proposed to use an open-source tool for managing consents and data use agreements that was previously developed for consent management of biological samples [48].…”

Section: Data Privacy and Data Access Governancementioning

confidence: 99%

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The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare

Cuggia

Combes

2019

Yearb Med Inform

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Objective: The diversity and volume of health data have been rapidly increasing in recent years. While such big data hold significant promise for accelerating discovery, data use entails many challenges including the need for adequate computational infrastructure and secure processes for data sharing and access. In Europe, two nationwide projects have been launched recently to support these objectives. This paper compares the French Health Data Hub initiative (HDH) to the German Medical Informatics Initiatives (MII). Method: We analysed the projects according to the following criteria: (i) Global approach and ambitions, (ii) Use cases, (iii) Governance and organization, (iv) Technical aspects and interoperability, and (v) Data privacy access/data governance. Results: The French and German projects share the same objectives but are different in terms of methodologies. The HDH project is based on a top-down approach and focuses on a shared computational infrastructure, providing tools and services to speed projects between data producers and data users. The MII project is based on a bottom-up approach and relies on four consortia including academic hospitals, universities, and private partners. Conclusion: Both projects could benefit from each other. A Franco-German cooperation, extended to other countries of the European Union with similar initiatives, should allow sharing and strengthening efforts in a strategic area where competition from other countries has increased.

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Section: Discussionmentioning

confidence: 99%

Section: Data Privacy and Data Access Governancementioning

confidence: 99%

The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare

Cuggia

Combes

2019

Yearb Med Inform

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“…In CDM, all aspects of requirements, such as data acquisition, standardized storage, integration of decentralized data capture, use and access, and data export for scientific analyses are combined and can be used sustainably. 6,11 Advantages of CDM are the shared usage of harmonized IT infrastructures, the data security, the possibility to check and improve data quality, and standardized data exports. 11 The CDM infrastructure and DZHK-wide harmonization and standardization enable a high data security.…”

Section: Discussionmentioning

confidence: 99%

“…The TORCH data protection concept is based on the template of the MOSAIC project. 5,6 It regulates individual TORCH-specific aspects to be considered in the main study centre and the individual recruiting study centres regarding data protection and safety. The concept was positively evaluated by the TMF in March 2015.…”

Section: Data Protectionmentioning

confidence: 99%

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

et al. 2017

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

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“…Since the ESSCA data collection platform was established, more comprehensive approaches towards decentralized data collection have been developed and published. Record linkage tools like the TMF PID Generator [24], the Mainzelliste [25], or the MOSAIC E-PIX service [26] provide methods for the centralized management of patient pseudonyms and allow to merge records when patients have been examined in multiple participating centres. The deployment of such a centralized ID management service, however, raises the barrier to entry in a distributed scenario with different data entry solutions in multiple countries that need to be integrated.…”

Section: Discussionmentioning

confidence: 99%

Registries in Clinical Epidemiology: the European Surveillance System on Contact Allergies (ESSCA)

Uter¹,

Schnuch²,

Wilkinson³

et al. 2016

Methods Inf Med

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SummaryBackground: Disease registries rely on consistent electronic data capturing (EDC) pertinent to their objectives; either by using existing electronic data as far as available, or by implementing specific software solutions.Objectives: To describe the current practice of an international disease registry (European Surveillance System on Contact Allergies, ESSCA, www.essca-dc.org) against different state of the art approaches for EDC.Methods: Since 2002, ESSCA is collecting data, currently from 53 departments in 12 countries. Departmental EDC software ranges from spreadsheets to comprehensive “patch test software” based on a relational database. In the Erlangen data centre, such diverse data is imported, converted to a common format, quality checked and pooled for scientific analyses.Results: Feed-back to participating departments for quality control is provided by standardised reports. Varying author teams publish scientific analyses addressing the objective of contact allergy surveillance.Conclusions: Although ESSCA represents a historically grown, heterogeneous network and not one unified approach to EDC, some of its features have contributed to its viability in the last 12 years and may be useful to consider for similar investigator-initiated networks.

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MOSAIC – A Modular Approach to Data Management in Epidemiological Studies

Cited by 33 publications

References 13 publications

The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare

The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare

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

Registries in Clinical Epidemiology: the European Surveillance System on Contact Allergies (ESSCA)

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