What does 'percent completeness' measure in data quality indicators?

What does 'percent completeness' measure in data quality indicators?

• A. Proportion of records with a given key field filled
• B. Proportion of records with correct coding
• C. Proportion of records from different hospitals
• D. Proportion of records linked to mortality data

Answer: (B)

Completeness is about whether a data field has a value for each record. It measures how much of the required information is actually present in the dataset. The percent completeness for a field is calculated by taking the number of records where that field is not missing, divided by the total number of records, times 100. In a cancer registry, you care about having essential fields filled (like diagnosis date, site, stage, etc.), because analyses rely on those values being present. That’s why the option describing the proportion of records with a given key field filled matches the concept of completeness. The other ideas refer to different data quality aspects. Correct coding speaks to accuracy or validity of the data values, not merely whether a value exists. Records from different hospitals describe coverage or representativeness, not the presence of data in a field. Proportion of records linked to mortality data concerns linkage, a specific type of data integration, rather than the general presence of data in a field.

Completeness is about whether a data field has a value for each record. It measures how much of the required information is actually present in the dataset. The percent completeness for a field is calculated by taking the number of records where that field is not missing, divided by the total number of records, times 100.

In a cancer registry, you care about having essential fields filled (like diagnosis date, site, stage, etc.), because analyses rely on those values being present. That’s why the option describing the proportion of records with a given key field filled matches the concept of completeness.

The other ideas refer to different data quality aspects. Correct coding speaks to accuracy or validity of the data values, not merely whether a value exists. Records from different hospitals describe coverage or representativeness, not the presence of data in a field. Proportion of records linked to mortality data concerns linkage, a specific type of data integration, rather than the general presence of data in a field.