Follow-Up & Data Management Flashcards

A cancer registrar is auditing data and finds that 12% of cases have no follow-up documented for over 24 months. Which corrective action is most appropriate?

Answer: Initiate an active tracing protocol using available contact and database resources

When cases lack recent follow-up, the registrar should initiate active tracing before assigning any vital status code.

Under STORE (Surveillance, Epidemiology, and End Results) guidelines, which event triggers an update to a patient's follow-up record?

Answer: Any new primary cancer diagnosis

A new primary cancer diagnosis requires an update to the follow-up record, and a new abstract may also be required.

When a registry uses record linkage with state vital statistics files to update vital status, this process is an example of:

Answer: Passive follow-up

Linking registry records with vital statistics files to update vital status without direct patient contact is the definition of passive follow-up.

A registrar discovers two abstracts in the database for the same patient with different medical record numbers. What is this situation called?

Answer: Duplicate record

Two records for the same patient are called duplicates, and merging or deduplicating them is essential for data integrity.

Which best describes the purpose of the 'Date of Death' field in a tumor registry abstract?

Answer: Captures the actual date the patient died for survival analysis

Date of death is used in survival calculations and must reflect the actual date the patient died, not administrative dates.

A hospital cancer registry wants to improve its follow-up rate. Which resource would MOST effectively supplement physician office contacts?

Answer: State cancer registry linkages and the National Death Index

State cancer registry linkages and NDI are the most authoritative and widely used supplemental resources for determining vital status.

In the context of cancer registry data management, 'edit checks' primarily serve to:

Answer: Detect and flag inconsistent or out-of-range data values

Edit checks are automated rules that identify data entries that are logically inconsistent, missing, or outside acceptable value ranges.