Understanding Data Quality

Data quality is the degree to which data are fit for their intended use. In clinical research, intended use includes participant safety oversight, protocol compliance, statistical analysis, regulatory reporting, publication, data sharing, and long-term archival. Data quality is therefore not a single property and cannot be judged only by whether a dataset contains values. A dataset may be complete but inaccurate, accurate but late, valid but poorly documented, or internally consistent but not suitable for answering the study question.