By George Curta · Last updated 2026-04-07
HIPAA-Ready PHI Anonymization for Healthcare
Healthcare breaches are the costliest across all industries—15 consecutive years. anonym.legal detects all 18 HIPAA identifiers, provides reversible encryption for approved research re-identification, and offers full audit trails for OCR investigations.
The Challenge
Healthcare organizations face strict requirements for patient data protection:
- •HIPAA requires protection of 18 PHI identifiers
- •Research datasets must be fully de-identified
- •Administrative documents contain patient information
- •Inter-facility data sharing requires consistent protection
The Solution
Comprehensive PHI detection and anonymization aligned with HIPAA requirements.
Healthcare Leads in Breach Costs
For 15 consecutive years, healthcare has had the highest average breach cost of any industry. Every PHI record exposed adds to regulatory fines, legal fees, and reputational damage.
| Industry | Avg. Breach Cost | Cost per Record |
|---|---|---|
| Healthcare | $7.42M | $533 |
| Financial Services | $5.90M | $219 |
| Pharmaceuticals | $5.01M | $188 |
| Global Average | $4.45M | $165 |
Source: IBM Cost of a Data Breach Report 2024
Complete HIPAA Identifier Coverage
anonym.legal detects and anonymizes all 18 HIPAA-defined identifiers, ensuring Safe Harbor compliance for de-identified health information.
The Solution
PHI Detection
Detect all 18 HIPAA-defined PHI types including medical record numbers, health plan IDs, and biometric identifiers.
Research Ready
Generate de-identified datasets for research that meet Safe Harbor requirements.
Audit Trails
Complete logging of all anonymization operations for compliance reporting.
Healthcare Formats
Support for clinical notes, administrative records, and structured health data.
Reversible for Approved Re-identification
Medical research often requires linking de-identified datasets back to patient records for longitudinal studies. anonym.legal's reversible encryption allows IRB-approved re-identification while maintaining HIPAA compliance during analysis phases.
- Longitudinal Studies: Re-link patient data across multi-year research
- Clinical Trials: Match anonymized trial data to outcomes
- IRB Compliance: Full audit trail for ethics board review
Research Workflow
Encrypt PHI with AES-256-GCM
Original data protected with encryption key
Share de-identified dataset
Researchers work with anonymized data
IRB-approved re-identification
Decrypt specific records when ethically approved
Complete audit trail
Full logging for compliance documentation
Related Resources
HIPAA Compliance Handbook
Complete guide covering all 18 PHI identifiers, Safe Harbor, and OCR audit preparation.
$7.42M: Why Healthcare Breaches Cost More
Analysis of 2025 breach data and prevention strategies.
Medical Research & IRB Compliance
How research institutions use reversible encryption for longitudinal studies.
Trusted by healthcare organizations
Protect Patient Data Today
Contact us to discuss your healthcare anonymization requirements.
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.
Related reading
- Common questions
- Glossary
- How tokens work
- Security posture
- Where we comply
- What we detect
- Case studies
- Release notes
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
- Open the web app and try a sample file.
- Learn how credits get counted.
- See current plans and limits.
- Meet the team behind the product.
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.