Anonymising Clinical Input to Coroners' Inquest Records – UK GDPR-compliant anonymisation per Common Law Duty of Confidentiality

Coroners' inquests generate clinical documentation — post-mortem reports, treating clinician statements, and medical records disclosed to the inquest — that identifies the deceased, their family members, and named clinicians. The Common Law Duty of Confidentiality continues to apply to clinical information disclosed in coronial proceedings. anonym.legal pseudonymises personal identifiers while preserving the clinical chronology and cause-of-death analysis for legal review and learning-from-deaths purposes.

When this applies

This task applies when clinical material submitted to or produced for a coroner's inquest is reviewed for learning-from-deaths analysis, Trust-level Mortality Review, or academic study of coronial outcomes, and the reviewing team requires the clinical content but not the identities of the deceased or named witnesses.

  1. Upload inquest clinical documents — post-mortem reports, clinician statements, and disclosed medical records — to anonym.legal.
  2. The engine identifies the deceased's name, date of birth, address, and NHS number, together with the names of named family members, treating clinicians, and any witnesses.
  3. Each named individual is pseudonymised consistently across all documents in the batch.
  4. Cause-of-death narrative, clinical timeline, post-mortem findings, and any identified learning points are preserved in clear text.
  5. A mapping table is produced with UK data residency.

What you provide

  • Post-mortem report
  • Treating clinician witness statements
  • Disclosed medical records submitted to the inquest

Limitations & cautions

  • Material formally produced in open coronial proceedings becomes a matter of public record — pseudonymisation is appropriate for internal learning review rather than suppression of publicly available inquest findings.
  • The tool does not assess the clinical causation analysis in the post-mortem report — obtain independent pathological review for disputed findings.
  • Named expert witnesses in the inquest are pseudonymised; confirm that role context sufficient for the learning review is preserved.

FAQ

Does the Common Law Duty of Confidentiality apply to records of a deceased patient?

The duty of confidentiality in English law continues to apply to the medical records of deceased patients. Information disclosed in coronial proceedings may be used for the purposes of the inquest; further use for learning or research requires appropriate governance.

Can the pseudonymised inquest materials be used in a Trust Mortality Review report?

Yes. This is a primary use case. The pseudonymised materials allow the Mortality Review panel to assess clinical care quality without processing personally identifiable data about the deceased or their family.

Are family members mentioned in clinician statements pseudonymised?

Yes. Named family members appearing in clinician statements as collateral historians or next of kin are detected and pseudonymised with distinct pseudonyms.

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.