Anonymising Whistleblowing & FTSU Disclosures – UK GDPR-compliant anonymisation per Common Law Duty of Confidentiality

Freedom-to-Speak-Up and whistleblowing disclosures in NHS and private healthcare settings frequently reference patient cases to evidence clinical concerns, embedding patient identifiers within reports that are shared with governance teams, regulators, or employment tribunals. The Common Law Duty of Confidentiality applies to clinical information in these disclosures. anonym.legal pseudonymises patient and third-party identifiers while preserving the clinical and governance substance of the concern raised.

When this applies

This task applies when a Freedom-to-Speak-Up disclosure or whistleblowing report is reviewed by HR governance teams, NHS England Freedom-to-Speak-Up Guardians, or employment legal advisers, and those reviewers require the substance of the clinical concern but not the identity of the individual patients referenced as examples.

  1. Upload the Freedom-to-Speak-Up disclosure or whistleblowing report to anonym.legal.
  2. The engine identifies patient names, dates, ward or clinic identifiers linked to named individuals, and the names of any clinical staff identified in the report.
  3. Each named patient and identified staff member is pseudonymised consistently; the concern narrative and supporting evidence remain in clear text.
  4. Dates, clinical incident descriptions, and governance references are preserved.
  5. The speaking-up worker's identity is handled according to the configured disclosure level — their identity may be preserved or pseudonymised depending on the review purpose.
  6. A mapping table is produced with UK data residency.

What you provide

  • Freedom-to-Speak-Up or whistleblowing disclosure report
  • Any supporting correspondence or clinical evidence attached to the disclosure

Limitations & cautions

  • Whistleblowing disclosures may engage employment law protections under the Public Interest Disclosure Act 1998; the tool pseudonymises personal data but does not assess the legal effect of the disclosure or any protected-disclosure status.
  • The clinical confidentiality of referenced patients is protected; however, the worker's identity may be protected by separate employment law provisions — confirm the appropriate handling of worker identity with employment legal counsel.

FAQ

Should the speaking-up worker's identity be pseudonymised in the review copy?

That depends on the review purpose. For the Freedom-to-Speak-Up Guardian's initial triage, the worker's identity may be known; for wider governance review, pseudonymising the worker's identity protects confidentiality. Configure the engine's worker-identity handling to match the review context.

Can patient identifiers in whistleblowing disclosures be pseudonymised without the patient's consent?

Processing patient identifiers in an internal governance review is likely to fall within the health and social care purposes basis in DPA 2018 Schedule 1 Part 1. The Common Law Duty of Confidentiality applies; confirm the lawful basis and the purpose limitation with your Data Protection Officer.

Does the tool handle disclosures that reference multiple patient cases?

Yes. Multiple patient cases referenced in a single disclosure are each pseudonymised with distinct, consistent pseudonyms throughout the document.

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.