Which data quality dimension is exemplified by missing onset dates in outbreak surveillance data?

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Study for the AMMO CDC Module 6 Test. Prepare with flashcards and multiple choice questions; each question includes hints and explanations. Gear up for your exam!

Multiple Choice

Which data quality dimension is exemplified by missing onset dates in outbreak surveillance data?

Explanation:
Completeness describes whether every required data field has a value. Missing onset dates indicate incomplete records, since an essential field is absent. In outbreak surveillance, having onset dates is crucial for constructing the epidemic curve and understanding the timing of cases; without them, the data are incomplete and less actionable. While validity, timeliness, and accuracy concern format/valid values, reporting speed, and truthfulness of values respectively, the specific issue here is the absence of a required data element, which is a hallmark of incompleteness.

Completeness describes whether every required data field has a value. Missing onset dates indicate incomplete records, since an essential field is absent. In outbreak surveillance, having onset dates is crucial for constructing the epidemic curve and understanding the timing of cases; without them, the data are incomplete and less actionable. While validity, timeliness, and accuracy concern format/valid values, reporting speed, and truthfulness of values respectively, the specific issue here is the absence of a required data element, which is a hallmark of incompleteness.

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