What activity measures data consistency?

• A. Data integrity audit
• B. Reliability study
• C. Data validation
• D. Data matching

Answer: (B)

Data consistency means that measurements stay the same when repeated under the same conditions or by different observers. A reliability study is designed to assess exactly this: how stable or repeatable the data are across repeated measurements or raters. By having measurements done multiple times or by multiple observers and then evaluating how well they agree, you get a quantifiable sense of data consistency. In cancer data management, this helps ensure that measurements like tumor size, pathology assessments, or reporting of outcomes are not bouncing around due to random error or variability in who or when the measurement is taken.

The other activities address related but broader or different aspects. A data integrity audit looks at overall quality and coherence of data rather than specifically quantifying repeatability. Data validation checks that values conform to rules and formats, which is about correctness of individual entries rather than consistency across repetitions. Data matching is about linking records that refer to the same entity across datasets, not about the consistency of measurements over time or across observers.

So, the activity that directly measures data consistency is the reliability study.