Profiling Clinical Datasets for Data Quality Assessment and Improvement

Clinical datasets are the most critical resources or assets in the repository of Electronic Health Records (EHRs) and their quality gains competitive advantages in translational research. Accurate, reliable, and consistent representation of clinical datasets are essential for answering key research questions. However, a major issue with carrying out research on routinely collected primary care datasets is that they are often not fit-for-purpose or research-ready. It often takes months (if not years) for researchers to clean and transform clinical datasets for meaningful translational research. Profiling clinical datasets provides a proactive approach to examining and understanding the content, context and structure of source system data. The objective of this study was to develop a profiling dashboard to monitor, measure, assess, and improve the quality of clinical datasets hosted and maintained by the Health Informatics Centre (HIC) at the University of Dundee. Preliminary results indicated that the dashboard affords the flexibility to perform objective assessment of data quality, in terms of accessibility, accuracy, appropriate amount of data, completeness, and consistency.