A formal procedure to check data accuracy against source documents is referred to as what?

A formal procedure to check data accuracy against source documents is referred to as what?

• A. Data audit
• B. Quality assurance
• C. Reabstracting study
• D. Data validation

Answer: (C)

The correct answer is a formal procedure to check data accuracy against source documents, which is referred to as a data audit. A data audit involves a systematic examination of the data collection processes and data sets to ensure that the data reported is accurate, complete, and consistent with the source documents from which it was derived. This process is essential in cancer registry operations because it helps identify discrepancies and ensures high data quality for subsequent analyses and reporting. Quality assurance is a broader concept that encompasses the protocols and procedures implemented to ensure that data meets specific quality standards throughout its lifecycle, but it does not specifically refer to the act of verifying against source documents. A reabstracting study involves taking a sample of previously collected data and re-evaluating it based on the original data collection criteria, rather than directly checking against source documents. It serves as a tool for quality assessment but is different from the direct verification process described. Data validation is an important step in data management that ensures data is within acceptable limits and conforms to predefined formats or rules, but it is not strictly a procedure for checking accuracy against source documents in the same manner as a data audit.

The correct answer is a formal procedure to check data accuracy against source documents, which is referred to as a data audit. A data audit involves a systematic examination of the data collection processes and data sets to ensure that the data reported is accurate, complete, and consistent with the source documents from which it was derived. This process is essential in cancer registry operations because it helps identify discrepancies and ensures high data quality for subsequent analyses and reporting.

Quality assurance is a broader concept that encompasses the protocols and procedures implemented to ensure that data meets specific quality standards throughout its lifecycle, but it does not specifically refer to the act of verifying against source documents.

A reabstracting study involves taking a sample of previously collected data and re-evaluating it based on the original data collection criteria, rather than directly checking against source documents. It serves as a tool for quality assessment but is different from the direct verification process described.

Data validation is an important step in data management that ensures data is within acceptable limits and conforms to predefined formats or rules, but it is not strictly a procedure for checking accuracy against source documents in the same manner as a data audit.