Drug Utilization Review Anonymization with anonym.plus

Strip patient IDs from the utilization data while the patterns stay.

DUR anonymization is the removal of all 18 HIPAA Safe Harbor IDs (45 CFR §164.514(b)) from a utilization dataset. anonym.plus does this locally. The use patterns and prescriber-level data stay; no row names the patient.

When this applies

A utilization dataset ties fill patterns to named patients. For a use review or a quality study, you strip the IDs but keep the patterns and the timing.

How anonym.plus handles it

  1. Point anonym.plus at the dataset on your device.
  2. It scans ID columns and any free-text fields.
  3. Patient names, MRNs, and dates get flagged.
  4. Confirm the flags; the medicines stay as non-IDs.
  5. Swap IDs with a steady map to keep cohort links.
  6. Save the clean data; the source stays on your machine.

What you need to provide

PHI entity types detected

Categoryanonym.plus entity typeExample
NamesPERSONpatient_name → [PATIENT_n]
Record IDsMEDICAL_RECORD_NUMBERmrn field → [MRN_n]
DatesDATE_TIMEfill dates → shifted [DATE]
LocationLOCATIONzip field → [ZIP]
AgeAGEage 92 → [AGE_BAND]
IdentifiersNATIONAL_IDplan no. → [ID]

Compliance achieved

Anonymize utilization datasets offline — see plans & start free →

Limitations & cautions

Ages over 89 must be banded under Safe Harbor, and a full zip cut to three digits. The medicines and patterns stay. Check that date-shift keeps the gaps your study needs before a full run.

Frequently asked questions

Can cohorts stay linkable after the swap?

Yes. A steady label map swaps each ID the same way, so a patient's rows still group while no real identity is left.

How are very old ages handled?

Safe Harbor caps age at 89, so any age above that is banded. The tool flags it as AGE for you to band.

Are the medicines kept?

Yes. Drug names are not identifiers, so they stay and the use patterns remain readable.