Background: Clinical research registries are rarely driven by data quality assurance. However, quality of data can have a huge impact on the performance and outcome of any given trial using registry data. Therefore, data quality assurance procedures for cost reduction and data process improvements have to be implemented in research registries.



Hypothesis: This research proposes that web-based data quality feedback can motivate registry users, increase their contributions and ultimately improve the quality of registry data and its (re-)use to support clinical trials; thereby reducing the costs and need for study monitors.



Method: To explore causes of low data quality and user motivation, a survey and an assessment of quality indicators in a multicentre clinical setting was performed. Subsequently, a development and evaluation of a web-based feedback framework was conducted. This was explored in the international Niemann-Pick disease registry (INPDR) and two clinical trials associated with the European Network for the Study of Adrenal Tumours (ENSAT).



Results: The survey and framework evaluation highlight effectiveness of web-based automated data quality feedback. Case studies showed an increase of data quality within observation time.



Conclusion: Centralised data monitoring requires a general framework that can be adjusted for a variety of trials and studies. This research highlights how biomedical research registries have to be designed with focus on data quality and feedback mechanisms

Glöckner, Stephan

Ⓒ  2016 Dr Stephan GlöcknerBackground

Biomedical research typically relies on data collected from patients in clinical settings. This is currently a fraught process due to the diversity and heterogeneity of data management systems, the numerous data standards and the sensitivities around the access to and sharing of such data. To tackle this, international biomedical registries are often established and targeted to specific diseases and communities. The quality of the data in such registries is essential to ensure that the clinical research findings can be translated into clinical care. However, at present clinical data management systems developed for biomedical research rarely perform quality assurance procedures during ongoing data collection. Similarly, clinical trials typically perform data quality assessment at the end of the trial. This is too late. We argue that data quality assurance procedures for cost reduction and data process improvements have to be implemented as an integral and ongoing part of disease registries and the data that they are used to collect. 

Such an approach requires all aspects of data collection efforts are considered including the intrinsic and extrinsic motivational factors of data entry personnel and the organisations in which they work. Technical solutions that encourage better behaviour and hence improve data quality are thus encouraged.

Hypothesis

The web-based interactions between data entry users and data management systems can be used to improve data quality. Leveraging technological advancement of web-based registries, new feedback mechanisms can be used to improve the overall data quality of the data that is captured by registries. This should lead to streamlined and improved data capture methods that support the users and ultimately benefit the clinical research more generally. This thesis proposes that web-based data quality feedback can motivate registry data entry personnel, increase their contributions and ultimately improve the quality of registry data and its (re-)use to support clinical trials.

Methods

To explore causes of low data quality and user motivation, a survey and an assessment of quality indicators in a multicentre clinical setting was performed. Based on this, we developed and evaluated a stage wise framework for web-based feedback and measured data quality trends including the factors that can impact user motivation in their data entry. This was explored in the International Niemann-Pick Disease Registry (INPDR) and two major international clinical trials associated with the European Network for the Study of Adrenal Tumours (ENSAT). We also considered the role of patients in data collection through mobile applications supporting data collection with the context of the Environmental Determinants of Islet Auto-immunity (ENDIA) clinical study.

Results

Researchers are motivated when they see the contribution resulting from their data entry and the improvement in treatment of patients. The results of the survey and the framework evaluation highlight the effectiveness of web-based automated data quality feedback. It was discovered that data quality feedback to researchers and the research community improve the data quality. Case studies showed an increase of data quality over the period of observation of this research – noting that these studies are still ongoing. The stage wise framework to evaluate data entry user behaviour after feedback was applied to one trial, which showed that feedback encouraged users to enter both more and higher quality data.

Conclusions

Recent literature confirms the need for data quality feedback as an ongoing and near-real time activity associated with data capture. Centralised data monitoring requires a general framework that can be adjusted for a variety of trials and studies. The proposed stage wide research method must be improved to measure the outcome of data quality feedback against a control group and/or where known benchmarks exist.

Data quality dimensions need to be adjusted to all research interests. In the age of big data and mobile health possibilities, further research needs to be performed with regards to the upcoming challenges of data trustworthiness and record eligibility to tackle current and future research objectives. The findings highlight how biomedical research registries have to be designed with focus on data quality and feedback mechanisms

University of Melbourne Institutional Repository

Application of automated feedback for the improvement of data quality in web-based clinical collaborations

University of Birmingham Research Archive, E-theses Repository

http://etheses.bham.ac.uk//id/eprint/7620/2/Gl%C3%B6ckner17PhD.pdf

Application of automated feedback for the improvement of data quality in web-based clinical collaborations

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University of Melbourne Institutional Repository

University of Birmingham Research Archive, E-theses Repository