Anonymize electronic medical records for secondary use disclosures – CCPA/HIPAA-compliant de-identification per 45 CFR §164.502

Electronic medical records (EMRs) are protected health information subject to the use and disclosure rules of 45 CFR §164.502. Covered entities may only use or disclose PHI as permitted by the Privacy Rule. anonym.legal de-identifies EMR exports so they fall outside §164.502's scope, enabling secondary uses — quality improvement, benchmarking, vendor analytics — without triggering authorization requirements.

When this applies

Apply this workflow when an EMR extract is being prepared for secondary disclosure to a vendor, research partner, or analytics team and the disclosure does not qualify under any enumerated §164.502(a)(1) permission — making de-identification the appropriate compliance path.

  1. Export the EMR data in HL7 FHIR R4, CCD, or CSV format and upload to anonym.legal.
  2. The engine maps PHI fields across FHIR resource types — Patient, Encounter, Condition, MedicationRequest, Observation — identifying all identifier elements per the Safe Harbor standard at §164.514(b)(2).
  3. Patient identifiers (name, MRN, SSN, date of birth, address, phone, email) are removed or pseudonymized; dates are generalized to year-only.
  4. Clinical content — diagnosis codes (ICD-10-CM), procedure codes (CPT), medication names, lab result values — is retained as non-identifying clinical information.
  5. A transformation log is generated documenting each field transformation for compliance documentation.
  6. The de-identified FHIR bundle or CSV export is delivered for downstream use.

What you provide

  • EMR export file (HL7 FHIR R4 JSON, CCD XML, or CSV)
  • Field mapping or FHIR resource type list identifying PHI-bearing elements
  • Intended secondary use description (to confirm de-identification is the correct Privacy Rule pathway)

Limitations & cautions

  • De-identifying an EMR extract enables secondary use without HIPAA authorization, but the underlying treatment record in the EMR system remains PHI and must continue to be managed as such.
  • Free-text clinical notes in EMR systems may contain narrative PHI not captured in structured fields; ensure free-text fields are included in the de-identification scope.
  • State law medical confidentiality requirements may impose additional obligations beyond HIPAA federal minimums — this workflow addresses federal Privacy Rule compliance only.

FAQ

Does de-identifying an EMR extract eliminate the need for a BAA with the analytics vendor?

Yes, provided the vendor receives only the de-identified data and has no access to PHI at any stage. If the vendor performs any step that involves processing PHI — including the de-identification itself — a BAA is required for that step under 45 CFR §164.502(e).

Can de-identified EMR data be used for population health benchmarking?

Yes. Once de-identified under the Safe Harbor or Expert Determination standard, the data is no longer PHI and may be disclosed for population health benchmarking without patient authorization or Privacy Rule restrictions.

How does the engine handle FHIR resources that reference patient identifiers in nested fields?

The engine traverses FHIR resource graphs and de-identifies all patient-referencing elements, including subject.reference, patient.reference, and performer.reference fields, not just top-level Patient resources. Nested identifiers in contained resources are also detected.

Healthcare Records

About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our servers live in Falkenstein, Germany.

We use Hetzner. They hold ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.