AI Associate Data for AI Practice Question
A healthcare AI model uses patient data. The legal team requires that all data used for training be de-identified according to HIPAA Safe Harbor method. Which data handling process satisfies this?
⚠ Common exam trap
It's easy for candidates to confuse de-identification with anonymization or pseudonymization, assuming that removing just names or aggregating data is sufficient, but Cisco tests the specific requirement of removing all 18 HIPAA identifiers under the Safe Harbor method.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Remove all 18 HIPAA identifiers from each record.
The HIPAA Safe Harbor method specifically requires the removal of all 18 identifiers listed in the HIPAA Privacy Rule from each patient record. This includes direct identifiers like names, addresses, and Social Security numbers, as well as indirect identifiers such as dates and geographic subdivisions. By removing these 18 identifiers, the data is considered de-identified and no longer subject to HIPAA restrictions, allowing it to be used for AI training.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Remove all 18 HIPAA identifiers from each record.
Why this is correct
Safe Harbor method requires removal of all listed identifiers.
- ✗
Generate synthetic data that mimics patient records.
Why it's wrong here
Synthetic data is not de-identification of original data.
- ✗
Remove patient names and replace with IDs.
Why it's wrong here
Other identifiers remain, like dates or ZIP codes.
- ✗
Anonymize data by aggregating into groups of 10 or more.
Why it's wrong here
Aggregation may not meet Safe Harbor's specific list.
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