Data quality significantly impacts the reliability and validity of empirical medical research. Specific measures can be used to check the quality of data during operation of a research project like a register. Furthermore these indicators allow an assessment of data quality independently from the institution responsible for data recording. A previously developed set of 24 data quality indicators was compared with measures of three research projects, each representing a specific view on the topic. The structure of the set was confirmed, being able to capture most of the projects' measures under the headings plausibility, organization, and correctness. Solely two indicators about metadata could not be appropriately mapped. However, several measures not considered so far were added to reach a number of 51 quality indicators in a first draft of a revised set. Most of the new indicators refine existing ones; e. g. the indicator "allowed values for missings" refines the existing indicator "allowed values for qualitative data elements". Seven projects' measures contribute supplementary aspects of data quality. The draft of the revised set of quality indicators will now be reviewed within and beyond the group.
|Journal||Studies in Health Technology and Informatics|
|Number of pages||5|
|Publication status||Published - 2012|