Pseudonymising Adult Safeguarding Case Files – UK GDPR-compliant anonymisation per DPA 2018 Sch.1 Pt.1

An adult safeguarding case file is a multi-agency record under the Care Act 2014 s.42 enquiry framework, identifying the adult at risk, alleged perpetrators, and professionals within special-category health data under DPA 2018 Schedule 1 Part 1. The CQC registers over 41,000 providers; records are retained for 8 years under NHS RMC 2023. anonym.legal pseudonymises all named individuals, preserving the safeguarding chronology and risk narrative.

When this applies

This task applies when adult safeguarding case files are reviewed by Safeguarding Adults Boards, academic researchers studying safeguarding patterns, or training developers creating case-study materials, and those parties require the safeguarding narrative but not identifiable information about the subject or named individuals. Breaches of confidentiality in safeguarding disclosures can attract fines of up to £17.5 million or 4% of annual global turnover under DPA 2018 s.157.

  1. Upload the safeguarding case file — chronology, risk assessments, and multi-agency correspondence — to anonym.legal.
  2. The engine identifies the adult at risk, alleged perpetrators, professional witnesses (social workers, nurses, police officers), and named family members across all documents.
  3. Each individual is pseudonymised with a consistent pseudonym; professional roles are preserved.
  4. The safeguarding chronology, risk-factor analysis, and outcome decisions are preserved in full.
  5. A mapping table is produced with UK data residency and role-based access control.
  6. The pseudonymised case file is released for the approved review or training purpose.

What you provide

  • Safeguarding case file chronology
  • Risk assessment and outcome documents
  • Multi-agency correspondence naming professionals and the adult at risk

Limitations & cautions

  • The tool does not assess the safeguarding risk level or the adequacy of the multi-agency response — obtain specialist safeguarding expertise.
  • Pseudonymised case files used for training must not be derived from a single real case without appropriate ethical oversight — consider synthetic case construction for training materials.
  • Named perpetrators in the case file are pseudonymised; the safeguarding outcome (including any criminal justice outcome) is preserved without identifying individuals. The NHS Records Management Code of Practice 2023 requires adult health records — including safeguarding records — to be retained for 8 years from the end of care.

FAQ

Can pseudonymised safeguarding files be shared with Safeguarding Adults Board statutory reviews?

Statutory reviews under the Care Act 2014 s.42 framework typically require identified records for the review panel. Pseudonymised files may be suitable for the learning-analysis phase after a Safeguarding Adults Review has concluded, subject to the SAR's data-sharing agreement. According to the ICO's 2021–22 guidance, pseudonymised records remain personal data under UK GDPR.

Are social worker and nurse names pseudonymised as well as the adult at risk?

Yes. All named individuals — the adult at risk, alleged perpetrators, social workers, nurses, and family members — are pseudonymised with distinct pseudonyms, preserving their roles and relationships without disclosing identities. The 8 Caldicott Principles (updated 2013, Principle 8 added 2020) require that data is shared only for justified purposes and with the minimum necessary information.

Does the tool handle files containing both health and social care records?

Yes. Multi-agency files containing NHS clinical records, local authority social care records, and police disclosure are processed in a single batch with consistent pseudonymisation across all sources. Care Act 2014 s.42 enquiries can generate case files running to hundreds of pages across over 41,000 registered care providers — efficient batch pseudonymisation reduces administrative burden.

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 company HQ is in Saarbrücken, Germany. Our servers run in Hetzner's Falkenstein datacenter.

Hetzner holds 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.