Datenqualität in der medizinischen Forschung: Leitlinie zum adaptiven Management von Datenqualität in Kohortenstudien und Registern

Nonnemacher, Michael; Nasseh, Daniel; Stausberg, Jürgen

doi:10.32745/9783954663743

Cited by 34 publications

(49 citation statements)

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“…Quality assurance (QA) will be based on the ‘Guidelines and Recommendations for Good Epidemiological Practice’ from the German Society of Epidemiology64 and the guideline for adaptive management of data quality in cohort studies and registries published by TMF (Technologie- und Methodenplattform für die vernetzte medizinische Forschung e.V.) 65…”

Section: Methods and Analysismentioning

confidence: 99%

Long-term outcomes in patients with severe depression after in-hospital treatment – study protocol of the depression long-term Augsburg (DELTA) study

et al. 2019

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IntroductionDepressive disorders are very common diseases entailing a great burden on affected people. However, comprehensive information on long-term disease course in patients with severe depression is lacking so far. The objectives of the DELTA study are to examine long-term outcomes and their predicting factors, to assess clinical response of antidepressant pharmacotherapy by applying therapeutic drug monitoring, to identify predictors of therapeutic non-response, to describe the long-term healthcare utilisation and to investigate the role of biomarkers in disease course.Methods and analysisA cohort study including all adult hospitalised cases (age range 18 to 75 years) of severe major depression who are admitted to the Bezirkskrankenhaus Augsburg is established. It is planned to include 300 patients. During the hospital stay, information is gathered through personal interview, self-administered questionnaires, cognitive tests and chart review. Furthermore, biomaterials are collected. After hospital discharge, patients are repeatedly re-examined over time (3, 6, 12, 24 and 36 months) to collect information about mortality, relapse, depression severity, health-related quality of life (HRQOL), perceived stigma, cognitive functions, diet, physical activity, treatment and healthcare utilisation. Follow-up blood samples are collected to determine therapeutic drug levels. The primary study aim is to investigate long-term therapeutic response, survival, relapse, HRQOL and cognitive functions. Survival time and time to relapse or re-hospitalisation will be analysed using Cox regression models. Changes of HRQOL, depressive symptoms and cognitive functions over time will be examined using generalised linear regression models for repeated measures or mixed models. Correlates of the disease course will be modelled using suitable generalised linear, mixed, estimating equation and growth curve models.Ethics and disseminationThe study protocol was approved by the Ethics Committee of the Ludwig-Maximilians-Universität München (date of approval: 23 October 2017, reference number: 17–625). Study results will be presented at scientific conferences and published in peer-reviewed scientific journals.

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Section: Methods and Analysismentioning

confidence: 99%

Long-term outcomes in patients with severe depression after in-hospital treatment – study protocol of the depression long-term Augsburg (DELTA) study

et al. 2019

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“…While we applied those metrics helpful to our specific DRN, there are many more to be considered. 14,56 The approach could be extended to allow running R-scripts from a secured script repository, allowing advanced users to evaluate any relevant metric. This can then be called upon by tools such as the QR-generator, incorporating the results of the scripts in an automated fashion.…”

Section: Limitations and Outlookmentioning

confidence: 99%

A Generic Method and Implementation to Evaluate and Improve Data Quality in Distributed Research Networks

et al. 2019

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Background With the increasing personalization of clinical therapies, translational research is evermore dependent on multisite research cooperations to obtain sufficient data and biomaterial. Distributed research networks rely on the availability of high-quality data stored in local databases operated by their member institutions. However, reusing data documented by independent health providers for the purpose of care, rather than research (“secondary use”), reveal a high variability in terms of data formats, as well as poor data quality, across network sites. Objectives The aim of this work is the provision of a process for the assessment of data quality with regard to completeness and syntactic accuracy across independently operated data warehouses using common definitions stored in a central (network-wide) metadata repository (MDR). Methods For assessment of data quality across multiple sites, we employ a framework of so-called bridgeheads. These are federated data warehouses, which allow the sites to participate in a research network. A central MDR is used to store the definitions of the commonly agreed data elements and their permissible values. Results We present the design for a generator of quality reports within a bridgehead, allowing the validation of data in the local data warehouse against a research network's central MDR. A standardized quality report can be produced at each network site, providing a means to compare data quality across sites, as well as to channel feedback to the local data source systems, and local documentation personnel. A reference implementation for this concept has been successfully utilized at 10 sites across the German Cancer Consortium. Conclusions We have shown that comparable data quality assessment across different partners of a distributed research network is feasible when a central metadata repository is combined with locally installed assessment processes. To achieve this, we designed a quality report and the process for generating such a report. The final step was the implementation in a German research network.

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“…At the national level, the Technology and Methods Platform for Networked Medical Research (TMF e.V.) has provided appropriate recommendations and a set of self-assessment indicators for various types of empirical research projects with its guideline on data QM [18]. ISO/IEC 27001, published in 2013, aims to bring information security under management control as part of the ISO/IEC 27000 family of standards [19].…”

Section: Fields Of Actionmentioning

confidence: 99%

Standardization in biobanking – between cooperation and competition

Meinung

Martin

Zimmermann³

2019

Journal of Laboratory Medicine

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Abstract This article presents the current situation of German biobanks and shows future fields of action in the European and international context on the basis of upcoming legal and normative challenges. It gives an overview of the development of the international biobank standard ISO 20387 and the commitment of German biobank experts in the ISO committee TC276. Less attention than the biobank standard per se has so far been paid to the basic mechanisms by which standards are developed and the potential of their application and accreditation. In this sense, this article deals with the motivation for active participation in standardization projects. We discuss the status of ISO 20387 as a conformity assessment standard and the consequence of accreditation as a performance monitor.

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Datenqualität in der medizinischen Forschung: Leitlinie zum adaptiven Management von Datenqualität in Kohortenstudien und Registern

Cited by 34 publications

References 0 publications

Long-term outcomes in patients with severe depression after in-hospital treatment – study protocol of the depression long-term Augsburg (DELTA) study

Long-term outcomes in patients with severe depression after in-hospital treatment – study protocol of the depression long-term Augsburg (DELTA) study

A Generic Method and Implementation to Evaluate and Improve Data Quality in Distributed Research Networks

Standardization in biobanking – between cooperation and competition

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